Overview

Dataset statistics

Number of variables29
Number of observations131
Missing cells116
Missing cells (%)3.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory29.8 KiB
Average record size in memory233.0 B

Variable types

Numeric9
Categorical20

Alerts

airdate has constant value "2020-12-18" Constant
_embedded_show_dvdCountry has constant value "nan" Constant
url has a high cardinality: 131 distinct values High cardinality
name has a high cardinality: 116 distinct values High cardinality
image has a high cardinality: 69 distinct values High cardinality
summary has a high cardinality: 54 distinct values High cardinality
_embedded_show_url has a high cardinality: 65 distinct values High cardinality
_embedded_show_name has a high cardinality: 65 distinct values High cardinality
_embedded_show_premiered has a high cardinality: 52 distinct values High cardinality
_embedded_show_officialSite has a high cardinality: 60 distinct values High cardinality
_embedded_show_summary has a high cardinality: 62 distinct values High cardinality
_links_self_href has a high cardinality: 131 distinct values High cardinality
runtime is highly correlated with _embedded_show_runtime and 1 other fieldsHigh correlation
_embedded_show_runtime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded_show_averageRuntime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded_show_weight is highly correlated with _embedded_show_updatedHigh correlation
_embedded_show_updated is highly correlated with _embedded_show_weightHigh correlation
season is highly correlated with number and 1 other fieldsHigh correlation
number is highly correlated with season and 1 other fieldsHigh correlation
runtime is highly correlated with _embedded_show_runtime and 1 other fieldsHigh correlation
_embedded_show_runtime is highly correlated with season and 3 other fieldsHigh correlation
_embedded_show_averageRuntime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded_show_weight is highly correlated with _embedded_show_updatedHigh correlation
_embedded_show_updated is highly correlated with _embedded_show_weightHigh correlation
runtime is highly correlated with _embedded_show_runtime and 1 other fieldsHigh correlation
_embedded_show_runtime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded_show_averageRuntime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded_show_officialSite is highly correlated with _embedded_show_ended and 14 other fieldsHigh correlation
_embedded_show_ended is highly correlated with _embedded_show_officialSite and 11 other fieldsHigh correlation
_embedded_show_name is highly correlated with _embedded_show_officialSite and 14 other fieldsHigh correlation
summary is highly correlated with type and 3 other fieldsHigh correlation
_embedded_show_summary is highly correlated with _embedded_show_officialSite and 14 other fieldsHigh correlation
_embedded_show_genres is highly correlated with _embedded_show_officialSite and 10 other fieldsHigh correlation
type is highly correlated with _embedded_show_officialSite and 8 other fieldsHigh correlation
_embedded_show_type is highly correlated with _embedded_show_officialSite and 7 other fieldsHigh correlation
airdate is highly correlated with _embedded_show_officialSite and 15 other fieldsHigh correlation
airtime is highly correlated with _embedded_show_officialSite and 9 other fieldsHigh correlation
_embedded_show_status is highly correlated with _embedded_show_officialSite and 10 other fieldsHigh correlation
_embedded_show_premiered is highly correlated with _embedded_show_officialSite and 14 other fieldsHigh correlation
image is highly correlated with _embedded_show_officialSite and 15 other fieldsHigh correlation
_embedded_show_url is highly correlated with _embedded_show_officialSite and 14 other fieldsHigh correlation
_embedded_show_language is highly correlated with _embedded_show_officialSite and 10 other fieldsHigh correlation
_embedded_show_dvdCountry is highly correlated with _embedded_show_officialSite and 15 other fieldsHigh correlation
airstamp is highly correlated with _embedded_show_officialSite and 10 other fieldsHigh correlation
id is highly correlated with airtime and 18 other fieldsHigh correlation
season is highly correlated with number and 11 other fieldsHigh correlation
number is highly correlated with season and 11 other fieldsHigh correlation
type is highly correlated with image and 8 other fieldsHigh correlation
airtime is highly correlated with id and 11 other fieldsHigh correlation
airstamp is highly correlated with id and 13 other fieldsHigh correlation
runtime is highly correlated with id and 17 other fieldsHigh correlation
image is highly correlated with id and 22 other fieldsHigh correlation
summary is highly correlated with type and 3 other fieldsHigh correlation
_embedded_show_id is highly correlated with id and 17 other fieldsHigh correlation
_embedded_show_url is highly correlated with id and 21 other fieldsHigh correlation
_embedded_show_name is highly correlated with id and 21 other fieldsHigh correlation
_embedded_show_type is highly correlated with id and 16 other fieldsHigh correlation
_embedded_show_language is highly correlated with id and 18 other fieldsHigh correlation
_embedded_show_genres is highly correlated with id and 19 other fieldsHigh correlation
_embedded_show_status is highly correlated with id and 16 other fieldsHigh correlation
_embedded_show_runtime is highly correlated with id and 19 other fieldsHigh correlation
_embedded_show_averageRuntime is highly correlated with id and 19 other fieldsHigh correlation
_embedded_show_premiered is highly correlated with id and 21 other fieldsHigh correlation
_embedded_show_ended is highly correlated with id and 17 other fieldsHigh correlation
_embedded_show_officialSite is highly correlated with id and 21 other fieldsHigh correlation
_embedded_show_weight is highly correlated with id and 16 other fieldsHigh correlation
_embedded_show_summary is highly correlated with id and 21 other fieldsHigh correlation
_embedded_show_updated is highly correlated with id and 16 other fieldsHigh correlation
number has 3 (2.3%) missing values Missing
runtime has 4 (3.1%) missing values Missing
image has 62 (47.3%) missing values Missing
_embedded_show_runtime has 45 (34.4%) missing values Missing
_embedded_show_averageRuntime has 2 (1.5%) missing values Missing
url is uniformly distributed Uniform
name is uniformly distributed Uniform
image is uniformly distributed Uniform
_links_self_href is uniformly distributed Uniform
id has unique values Unique
url has unique values Unique
_links_self_href has unique values Unique

Reproduction

Analysis started2022-05-10 02:16:14.001523
Analysis finished2022-05-10 02:16:49.825854
Duration35.82 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

id
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct131
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1999805.893
Minimum1910448
Maximum2176135
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2022-05-09T21:16:49.910376image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1910448
5-th percentile1962788.5
Q11978335
median1986252
Q31990512.5
95-th percentile2081201
Maximum2176135
Range265687
Interquartile range (IQR)12177.5

Descriptive statistics

Standard deviation45662.16892
Coefficient of variation (CV)0.02283330051
Kurtosis4.330316172
Mean1999805.893
Median Absolute Deviation (MAD)5855
Skewness1.999000465
Sum261974572
Variance2085033671
MonotonicityNot monotonic
2022-05-09T21:16:50.078544image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19681141
 
0.8%
19694891
 
0.8%
19739941
 
0.8%
19739931
 
0.8%
19739921
 
0.8%
19739911
 
0.8%
19739901
 
0.8%
19739891
 
0.8%
19739881
 
0.8%
19739871
 
0.8%
Other values (121)121
92.4%
ValueCountFrequency (%)
19104481
0.8%
19248901
0.8%
19400361
0.8%
19400411
0.8%
19442571
0.8%
19496361
0.8%
19610051
0.8%
19645721
0.8%
19670231
0.8%
19676971
0.8%
ValueCountFrequency (%)
21761351
0.8%
21538401
0.8%
21538391
0.8%
21538381
0.8%
21538371
0.8%
21327101
0.8%
20821761
0.8%
20802261
0.8%
20714861
0.8%
20714851
0.8%

url
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct131
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
https://www.tvmaze.com/episodes/1968114/po-sezonu-videodajdzest-seasonvar-6x51-vypusk-305
 
1
https://www.tvmaze.com/episodes/1969489/discipline-2x06-beyond-the
 
1
https://www.tvmaze.com/episodes/1973994/sweet-home-1x09-episode-9
 
1
https://www.tvmaze.com/episodes/1973993/sweet-home-1x08-episode-8
 
1
https://www.tvmaze.com/episodes/1973992/sweet-home-1x07-episode-7
 
1
Other values (126)
126 

Length

Max length131
Median length90
Mean length72.06870229
Min length51

Characters and Unicode

Total characters9441
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique131 ?
Unique (%)100.0%

Sample

1st rowhttps://www.tvmaze.com/episodes/1968114/po-sezonu-videodajdzest-seasonvar-6x51-vypusk-305
2nd rowhttps://www.tvmaze.com/episodes/1961005/cuma-2x08-seria-14
3rd rowhttps://www.tvmaze.com/episodes/1989253/to-so-sketci-1x07-7-vypusk
4th rowhttps://www.tvmaze.com/episodes/1988013/muzskaa-tema-1x02-seria-2
5th rowhttps://www.tvmaze.com/episodes/2030153/fox-spirit-matchmaker-9x03-episode-124

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1968114/po-sezonu-videodajdzest-seasonvar-6x51-vypusk-3051
 
0.8%
https://www.tvmaze.com/episodes/1969489/discipline-2x06-beyond-the1
 
0.8%
https://www.tvmaze.com/episodes/1973994/sweet-home-1x09-episode-91
 
0.8%
https://www.tvmaze.com/episodes/1973993/sweet-home-1x08-episode-81
 
0.8%
https://www.tvmaze.com/episodes/1973992/sweet-home-1x07-episode-71
 
0.8%
https://www.tvmaze.com/episodes/1973991/sweet-home-1x06-episode-61
 
0.8%
https://www.tvmaze.com/episodes/1973990/sweet-home-1x05-episode-51
 
0.8%
https://www.tvmaze.com/episodes/1973989/sweet-home-1x04-episode-41
 
0.8%
https://www.tvmaze.com/episodes/1973988/sweet-home-1x03-episode-31
 
0.8%
https://www.tvmaze.com/episodes/1973987/sweet-home-1x02-episode-21
 
0.8%
Other values (121)121
92.4%

Length

2022-05-09T21:16:50.233428image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1968114/po-sezonu-videodajdzest-seasonvar-6x51-vypusk-3051
 
0.8%
https://www.tvmaze.com/episodes/1990511/black-widows-1x08-purple-moments1
 
0.8%
https://www.tvmaze.com/episodes/1989253/to-so-sketci-1x07-7-vypusk1
 
0.8%
https://www.tvmaze.com/episodes/1988013/muzskaa-tema-1x02-seria-21
 
0.8%
https://www.tvmaze.com/episodes/2030153/fox-spirit-matchmaker-9x03-episode-1241
 
0.8%
https://www.tvmaze.com/episodes/1972569/the-wolf-1x27-episode-271
 
0.8%
https://www.tvmaze.com/episodes/1972570/the-wolf-1x28-episode-281
 
0.8%
https://www.tvmaze.com/episodes/1910448/the-founder-of-diabolism-q-1x22-escape1
 
0.8%
https://www.tvmaze.com/episodes/1998583/mr-right-is-here-1x11-episode-111
 
0.8%
https://www.tvmaze.com/episodes/1998584/mr-right-is-here-1x12-episode-121
 
0.8%
Other values (121)121
92.4%

Most occurring characters

ValueCountFrequency (%)
e808
 
8.6%
/655
 
6.9%
-618
 
6.5%
s602
 
6.4%
t566
 
6.0%
o496
 
5.3%
w455
 
4.8%
p363
 
3.8%
m353
 
3.7%
i352
 
3.7%
Other values (30)4173
44.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6357
67.3%
Decimal Number1418
 
15.0%
Other Punctuation1048
 
11.1%
Dash Punctuation618
 
6.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e808
12.7%
s602
 
9.5%
t566
 
8.9%
o496
 
7.8%
w455
 
7.2%
p363
 
5.7%
m353
 
5.6%
i352
 
5.5%
a333
 
5.2%
d288
 
4.5%
Other values (16)1741
27.4%
Decimal Number
ValueCountFrequency (%)
1336
23.7%
0206
14.5%
9190
13.4%
2148
10.4%
8127
 
9.0%
392
 
6.5%
586
 
6.1%
682
 
5.8%
479
 
5.6%
772
 
5.1%
Other Punctuation
ValueCountFrequency (%)
/655
62.5%
.262
 
25.0%
:131
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-618
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin6357
67.3%
Common3084
32.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e808
12.7%
s602
 
9.5%
t566
 
8.9%
o496
 
7.8%
w455
 
7.2%
p363
 
5.7%
m353
 
5.6%
i352
 
5.5%
a333
 
5.2%
d288
 
4.5%
Other values (16)1741
27.4%
Common
ValueCountFrequency (%)
/655
21.2%
-618
20.0%
1336
10.9%
.262
 
8.5%
0206
 
6.7%
9190
 
6.2%
2148
 
4.8%
:131
 
4.2%
8127
 
4.1%
392
 
3.0%
Other values (4)319
10.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII9441
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e808
 
8.6%
/655
 
6.9%
-618
 
6.5%
s602
 
6.4%
t566
 
6.0%
o496
 
5.3%
w455
 
4.8%
p363
 
3.8%
m353
 
3.7%
i352
 
3.7%
Other values (30)4173
44.2%

name
Categorical

HIGH CARDINALITY
UNIFORM

Distinct116
Distinct (%)88.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Episode 4
 
3
Episode 5
 
3
Episode 11
 
3
Episode 8
 
2
Episode 6
 
2
Other values (111)
118 

Length

Max length78
Median length43
Mean length14.05343511
Min length2

Characters and Unicode

Total characters1841
Distinct characters109
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique104 ?
Unique (%)79.4%

Sample

1st rowВыпуск 305
2nd rowСерия 14
3rd row7 выпуск
4th rowСерия 2
5th rowEpisode 124

Common Values

ValueCountFrequency (%)
Episode 43
 
2.3%
Episode 53
 
2.3%
Episode 113
 
2.3%
Episode 82
 
1.5%
Episode 62
 
1.5%
Episode 72
 
1.5%
Episode 92
 
1.5%
Episode 102
 
1.5%
Happy Hour2
 
1.5%
Episode 32
 
1.5%
Other values (106)108
82.4%

Length

2022-05-09T21:16:50.387391image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
episode34
 
10.5%
the10
 
3.1%
9
 
2.8%
54
 
1.2%
and4
 
1.2%
24
 
1.2%
184
 
1.2%
hour4
 
1.2%
84
 
1.2%
73
 
0.9%
Other values (212)243
75.2%

Most occurring characters

ValueCountFrequency (%)
192
 
10.4%
e166
 
9.0%
i110
 
6.0%
o100
 
5.4%
a100
 
5.4%
s90
 
4.9%
r74
 
4.0%
d68
 
3.7%
t63
 
3.4%
p59
 
3.2%
Other values (99)819
44.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1254
68.1%
Uppercase Letter262
 
14.2%
Space Separator192
 
10.4%
Decimal Number87
 
4.7%
Other Punctuation34
 
1.8%
Dash Punctuation5
 
0.3%
Other Letter2
 
0.1%
Final Punctuation1
 
0.1%
Initial Punctuation1
 
0.1%
Math Symbol1
 
0.1%
Other values (2)2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e166
13.2%
i110
 
8.8%
o100
 
8.0%
a100
 
8.0%
s90
 
7.2%
r74
 
5.9%
d68
 
5.4%
t63
 
5.0%
p59
 
4.7%
l59
 
4.7%
Other values (44)365
29.1%
Uppercase Letter
ValueCountFrequency (%)
E48
18.3%
S22
 
8.4%
T19
 
7.3%
D16
 
6.1%
P15
 
5.7%
C14
 
5.3%
H12
 
4.6%
R12
 
4.6%
B12
 
4.6%
O11
 
4.2%
Other values (17)81
30.9%
Decimal Number
ValueCountFrequency (%)
123
26.4%
213
14.9%
811
12.6%
09
 
10.3%
37
 
8.0%
76
 
6.9%
46
 
6.9%
55
 
5.7%
64
 
4.6%
93
 
3.4%
Other Punctuation
ValueCountFrequency (%)
,13
38.2%
.4
 
11.8%
:4
 
11.8%
#3
 
8.8%
&3
 
8.8%
!3
 
8.8%
"2
 
5.9%
'1
 
2.9%
?1
 
2.9%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
192
100.0%
Dash Punctuation
ValueCountFrequency (%)
-5
100.0%
Final Punctuation
ValueCountFrequency (%)
»1
100.0%
Initial Punctuation
ValueCountFrequency (%)
«1
100.0%
Math Symbol
ValueCountFrequency (%)
|1
100.0%
Close Punctuation
ValueCountFrequency (%)
)1
100.0%
Open Punctuation
ValueCountFrequency (%)
(1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1436
78.0%
Common323
 
17.5%
Cyrillic80
 
4.3%
Han2
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e166
 
11.6%
i110
 
7.7%
o100
 
7.0%
a100
 
7.0%
s90
 
6.3%
r74
 
5.2%
d68
 
4.7%
t63
 
4.4%
p59
 
4.1%
l59
 
4.1%
Other values (43)547
38.1%
Cyrillic
ValueCountFrequency (%)
и7
 
8.8%
о7
 
8.8%
е7
 
8.8%
к6
 
7.5%
р6
 
7.5%
с5
 
6.2%
л4
 
5.0%
п4
 
5.0%
ы4
 
5.0%
в3
 
3.8%
Other values (18)27
33.8%
Common
ValueCountFrequency (%)
192
59.4%
123
 
7.1%
213
 
4.0%
,13
 
4.0%
811
 
3.4%
09
 
2.8%
37
 
2.2%
76
 
1.9%
46
 
1.9%
55
 
1.5%
Other values (16)38
 
11.8%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1749
95.0%
Cyrillic80
 
4.3%
None10
 
0.5%
CJK2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
192
 
11.0%
e166
 
9.5%
i110
 
6.3%
o100
 
5.7%
a100
 
5.7%
s90
 
5.1%
r74
 
4.2%
d68
 
3.9%
t63
 
3.6%
p59
 
3.4%
Other values (61)727
41.6%
Cyrillic
ValueCountFrequency (%)
и7
 
8.8%
о7
 
8.8%
е7
 
8.8%
к6
 
7.5%
р6
 
7.5%
с5
 
6.2%
л4
 
5.0%
п4
 
5.0%
ы4
 
5.0%
в3
 
3.8%
Other values (18)27
33.8%
None
ValueCountFrequency (%)
ó2
20.0%
ø2
20.0%
ş1
10.0%
»1
10.0%
«1
10.0%
å1
10.0%
ä1
10.0%
í1
10.0%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%

season
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct11
Distinct (%)8.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean63.88549618
Minimum1
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2022-05-09T21:16:50.535543image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32.5
95-th percentile10
Maximum2020
Range2019
Interquartile range (IQR)1.5

Descriptive statistics

Standard deviation348.4974482
Coefficient of variation (CV)5.455032347
Kurtosis28.91511196
Mean63.88549618
Median Absolute Deviation (MAD)0
Skewness5.520122934
Sum8369
Variance121450.4714
MonotonicityNot monotonic
2022-05-09T21:16:50.640217image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
186
65.6%
612
 
9.2%
212
 
9.2%
36
 
4.6%
45
 
3.8%
20204
 
3.1%
102
 
1.5%
91
 
0.8%
171
 
0.8%
51
 
0.8%
ValueCountFrequency (%)
186
65.6%
212
 
9.2%
36
 
4.6%
45
 
3.8%
51
 
0.8%
612
 
9.2%
91
 
0.8%
102
 
1.5%
171
 
0.8%
181
 
0.8%
ValueCountFrequency (%)
20204
 
3.1%
181
 
0.8%
171
 
0.8%
102
 
1.5%
91
 
0.8%
612
9.2%
51
 
0.8%
45
3.8%
36
4.6%
212
9.2%

number
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct32
Distinct (%)25.0%
Missing3
Missing (%)2.3%
Infinite0
Infinite (%)0.0%
Mean18.0390625
Minimum1
Maximum345
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2022-05-09T21:16:50.781701image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q311
95-th percentile49.25
Maximum345
Range344
Interquartile range (IQR)8

Descriptive statistics

Standard deviation51.15152761
Coefficient of variation (CV)2.835597893
Kurtosis29.2619717
Mean18.0390625
Median Absolute Deviation (MAD)3
Skewness5.372553755
Sum2309
Variance2616.478777
MonotonicityNot monotonic
2022-05-09T21:16:50.922161image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
315
11.5%
513
 
9.9%
411
 
8.4%
611
 
8.4%
89
 
6.9%
29
 
6.9%
19
 
6.9%
77
 
5.3%
96
 
4.6%
105
 
3.8%
Other values (22)33
25.2%
ValueCountFrequency (%)
19
6.9%
29
6.9%
315
11.5%
411
8.4%
513
9.9%
611
8.4%
77
5.3%
89
6.9%
96
 
4.6%
105
 
3.8%
ValueCountFrequency (%)
3451
0.8%
3101
0.8%
3091
0.8%
1931
0.8%
691
0.8%
641
0.8%
511
0.8%
461
0.8%
381
0.8%
331
0.8%

type
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
regular
128 
significant_special
 
3

Length

Max length19
Median length7
Mean length7.27480916
Min length7

Characters and Unicode

Total characters953
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowregular
2nd rowregular
3rd rowregular
4th rowregular
5th rowregular

Common Values

ValueCountFrequency (%)
regular128
97.7%
significant_special3
 
2.3%

Length

2022-05-09T21:16:51.181088image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:16:51.342629image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
regular128
97.7%
significant_special3
 
2.3%

Most occurring characters

ValueCountFrequency (%)
r256
26.9%
a134
14.1%
e131
13.7%
g131
13.7%
l131
13.7%
u128
13.4%
i12
 
1.3%
s6
 
0.6%
n6
 
0.6%
c6
 
0.6%
Other values (4)12
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter950
99.7%
Connector Punctuation3
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r256
26.9%
a134
14.1%
e131
13.8%
g131
13.8%
l131
13.8%
u128
13.5%
i12
 
1.3%
s6
 
0.6%
n6
 
0.6%
c6
 
0.6%
Other values (3)9
 
0.9%
Connector Punctuation
ValueCountFrequency (%)
_3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin950
99.7%
Common3
 
0.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
r256
26.9%
a134
14.1%
e131
13.8%
g131
13.8%
l131
13.8%
u128
13.5%
i12
 
1.3%
s6
 
0.6%
n6
 
0.6%
c6
 
0.6%
Other values (3)9
 
0.9%
Common
ValueCountFrequency (%)
_3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII953
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r256
26.9%
a134
14.1%
e131
13.7%
g131
13.7%
l131
13.7%
u128
13.4%
i12
 
1.3%
s6
 
0.6%
n6
 
0.6%
c6
 
0.6%
Other values (4)12
 
1.3%

airdate
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2020-12-18
131 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters1310
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-18
2nd row2020-12-18
3rd row2020-12-18
4th row2020-12-18
5th row2020-12-18

Common Values

ValueCountFrequency (%)
2020-12-18131
100.0%

Length

2022-05-09T21:16:51.486640image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:16:51.779050image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-18131
100.0%

Most occurring characters

ValueCountFrequency (%)
2393
30.0%
0262
20.0%
-262
20.0%
1262
20.0%
8131
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number1048
80.0%
Dash Punctuation262
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2393
37.5%
0262
25.0%
1262
25.0%
8131
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-262
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1310
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2393
30.0%
0262
20.0%
-262
20.0%
1262
20.0%
8131
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1310
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2393
30.0%
0262
20.0%
-262
20.0%
1262
20.0%
8131
 
10.0%

airtime
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct6
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
nan
110 
20:00
 
11
12:00
 
5
06:00
 
3
21:00
 
1

Length

Max length5
Median length3
Mean length3.320610687
Min length3

Characters and Unicode

Total characters435
Distinct characters8
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)1.5%

Sample

1st rownan
2nd rownan
3rd row12:00
4th row12:00
5th rownan

Common Values

ValueCountFrequency (%)
nan110
84.0%
20:0011
 
8.4%
12:005
 
3.8%
06:003
 
2.3%
21:001
 
0.8%
19:001
 
0.8%

Length

2022-05-09T21:16:51.876663image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:16:51.986763image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
nan110
84.0%
20:0011
 
8.4%
12:005
 
3.8%
06:003
 
2.3%
21:001
 
0.8%
19:001
 
0.8%

Most occurring characters

ValueCountFrequency (%)
n220
50.6%
a110
25.3%
056
 
12.9%
:21
 
4.8%
217
 
3.9%
17
 
1.6%
63
 
0.7%
91
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter330
75.9%
Decimal Number84
 
19.3%
Other Punctuation21
 
4.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
056
66.7%
217
 
20.2%
17
 
8.3%
63
 
3.6%
91
 
1.2%
Lowercase Letter
ValueCountFrequency (%)
n220
66.7%
a110
33.3%
Other Punctuation
ValueCountFrequency (%)
:21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin330
75.9%
Common105
 
24.1%

Most frequent character per script

Common
ValueCountFrequency (%)
056
53.3%
:21
 
20.0%
217
 
16.2%
17
 
6.7%
63
 
2.9%
91
 
1.0%
Latin
ValueCountFrequency (%)
n220
66.7%
a110
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII435
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n220
50.6%
a110
25.3%
056
 
12.9%
:21
 
4.8%
217
 
3.9%
17
 
1.6%
63
 
0.7%
91
 
0.2%

airstamp
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct8
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2020-12-18T12:00:00+00:00
74 
2020-12-18T06:30:00+00:00
21 
2020-12-18T11:00:00+00:00
15 
2020-12-18T04:00:00+00:00
11 
2020-12-18T00:00:00+00:00
 
4
Other values (3)
 
6

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters3275
Distinct characters13
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.8%

Sample

1st row2020-12-18T00:00:00+00:00
2nd row2020-12-18T00:00:00+00:00
3rd row2020-12-18T00:00:00+00:00
4th row2020-12-18T00:00:00+00:00
5th row2020-12-18T04:00:00+00:00

Common Values

ValueCountFrequency (%)
2020-12-18T12:00:00+00:0074
56.5%
2020-12-18T06:30:00+00:0021
 
16.0%
2020-12-18T11:00:00+00:0015
 
11.5%
2020-12-18T04:00:00+00:0011
 
8.4%
2020-12-18T00:00:00+00:004
 
3.1%
2020-12-18T05:00:00+00:003
 
2.3%
2020-12-18T09:00:00+00:002
 
1.5%
2020-12-18T10:00:00+00:001
 
0.8%

Length

2022-05-09T21:16:52.130446image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:16:52.342318image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-18t12:00:00+00:0074
56.5%
2020-12-18t06:30:00+00:0021
 
16.0%
2020-12-18t11:00:00+00:0015
 
11.5%
2020-12-18t04:00:00+00:0011
 
8.4%
2020-12-18t00:00:00+00:004
 
3.1%
2020-12-18t05:00:00+00:003
 
2.3%
2020-12-18t09:00:00+00:002
 
1.5%
2020-12-18t10:00:00+00:001
 
0.8%

Most occurring characters

ValueCountFrequency (%)
01335
40.8%
2467
 
14.3%
:393
 
12.0%
1367
 
11.2%
-262
 
8.0%
8131
 
4.0%
T131
 
4.0%
+131
 
4.0%
621
 
0.6%
321
 
0.6%
Other values (3)16
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number2358
72.0%
Other Punctuation393
 
12.0%
Dash Punctuation262
 
8.0%
Uppercase Letter131
 
4.0%
Math Symbol131
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
01335
56.6%
2467
 
19.8%
1367
 
15.6%
8131
 
5.6%
621
 
0.9%
321
 
0.9%
411
 
0.5%
53
 
0.1%
92
 
0.1%
Other Punctuation
ValueCountFrequency (%)
:393
100.0%
Dash Punctuation
ValueCountFrequency (%)
-262
100.0%
Uppercase Letter
ValueCountFrequency (%)
T131
100.0%
Math Symbol
ValueCountFrequency (%)
+131
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common3144
96.0%
Latin131
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
01335
42.5%
2467
 
14.9%
:393
 
12.5%
1367
 
11.7%
-262
 
8.3%
8131
 
4.2%
+131
 
4.2%
621
 
0.7%
321
 
0.7%
411
 
0.3%
Other values (2)5
 
0.2%
Latin
ValueCountFrequency (%)
T131
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII3275
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
01335
40.8%
2467
 
14.3%
:393
 
12.0%
1367
 
11.2%
-262
 
8.0%
8131
 
4.0%
T131
 
4.0%
+131
 
4.0%
621
 
0.6%
321
 
0.6%
Other values (3)16
 
0.5%

runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct52
Distinct (%)40.9%
Missing4
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean31.63779528
Minimum1
Maximum120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2022-05-09T21:16:52.581129image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8
Q115
median28
Q345
95-th percentile58.4
Maximum120
Range119
Interquartile range (IQR)30

Descriptive statistics

Standard deviation19.85969408
Coefficient of variation (CV)0.6277205447
Kurtosis4.397595695
Mean31.63779528
Median Absolute Deviation (MAD)15
Skewness1.39466432
Sum4018
Variance394.4074491
MonotonicityNot monotonic
2022-05-09T21:16:52.869100image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4512
 
9.2%
2511
 
8.4%
1510
 
7.6%
85
 
3.8%
94
 
3.1%
504
 
3.1%
234
 
3.1%
203
 
2.3%
393
 
2.3%
353
 
2.3%
Other values (42)68
51.9%
(Missing)4
 
3.1%
ValueCountFrequency (%)
11
 
0.8%
41
 
0.8%
51
 
0.8%
61
 
0.8%
72
 
1.5%
85
3.8%
94
3.1%
103
2.3%
111
 
0.8%
122
 
1.5%
ValueCountFrequency (%)
1202
1.5%
721
0.8%
631
0.8%
601
0.8%
592
1.5%
572
1.5%
552
1.5%
541
0.8%
532
1.5%
522
1.5%

image
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct69
Distinct (%)100.0%
Missing62
Missing (%)47.3%
Memory size1.1 KiB
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/289/723314.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/289/723314.jpg'}
 
1
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/291/729311.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/291/729311.jpg'}
 
1
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/289/723290.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/289/723290.jpg'}
 
1
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/289/723530.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/289/723530.jpg'}
 
1
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/289/723317.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/289/723317.jpg'}
 
1
Other values (64)
64 

Length

Max length176
Median length176
Mean length176
Min length176

Characters and Unicode

Total characters12144
Distinct characters38
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique69 ?
Unique (%)100.0%

Sample

1st row{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/295/737762.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/295/737762.jpg'}
2nd row{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/289/724059.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/289/724059.jpg'}
3rd row{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/285/714187.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/285/714187.jpg'}
4th row{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/726352.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/726352.jpg'}
5th row{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/726073.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/726073.jpg'}

Common Values

ValueCountFrequency (%)
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/289/723314.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/289/723314.jpg'}1
 
0.8%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/291/729311.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/291/729311.jpg'}1
 
0.8%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/289/723290.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/289/723290.jpg'}1
 
0.8%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/289/723530.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/289/723530.jpg'}1
 
0.8%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/289/723317.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/289/723317.jpg'}1
 
0.8%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/289/723316.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/289/723316.jpg'}1
 
0.8%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/289/723315.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/289/723315.jpg'}1
 
0.8%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/289/723313.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/289/723313.jpg'}1
 
0.8%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/725568.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/725568.jpg'}1
 
0.8%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/289/723312.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/289/723312.jpg'}1
 
0.8%
Other values (59)59
45.0%
(Missing)62
47.3%

Length

2022-05-09T21:16:53.069594image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
medium69
25.0%
original69
25.0%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726073.jpg1
 
0.4%
https://static.tvmaze.com/uploads/images/medium_landscape/289/723299.jpg1
 
0.4%
https://static.tvmaze.com/uploads/images/original_untouched/289/723299.jpg1
 
0.4%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726075.jpg1
 
0.4%
https://static.tvmaze.com/uploads/images/original_untouched/290/726075.jpg1
 
0.4%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726074.jpg1
 
0.4%
https://static.tvmaze.com/uploads/images/original_untouched/290/726074.jpg1
 
0.4%
https://static.tvmaze.com/uploads/images/original_untouched/290/726073.jpg1
 
0.4%
Other values (130)130
47.1%

Most occurring characters

ValueCountFrequency (%)
/966
 
8.0%
a828
 
6.8%
t759
 
6.2%
m690
 
5.7%
i690
 
5.7%
s621
 
5.1%
e552
 
4.5%
'552
 
4.5%
o483
 
4.0%
p483
 
4.0%
Other values (28)5520
45.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter8142
67.0%
Other Punctuation2277
 
18.8%
Decimal Number1242
 
10.2%
Space Separator207
 
1.7%
Connector Punctuation138
 
1.1%
Close Punctuation69
 
0.6%
Open Punctuation69
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a828
 
10.2%
t759
 
9.3%
m690
 
8.5%
i690
 
8.5%
s621
 
7.6%
e552
 
6.8%
o483
 
5.9%
p483
 
5.9%
g414
 
5.1%
c414
 
5.1%
Other values (9)2208
27.1%
Decimal Number
ValueCountFrequency (%)
2300
24.2%
7200
16.1%
3154
12.4%
8150
12.1%
9144
11.6%
0112
 
9.0%
166
 
5.3%
648
 
3.9%
542
 
3.4%
426
 
2.1%
Other Punctuation
ValueCountFrequency (%)
/966
42.4%
'552
24.2%
.414
18.2%
:276
 
12.1%
,69
 
3.0%
Space Separator
ValueCountFrequency (%)
207
100.0%
Connector Punctuation
ValueCountFrequency (%)
_138
100.0%
Close Punctuation
ValueCountFrequency (%)
}69
100.0%
Open Punctuation
ValueCountFrequency (%)
{69
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8142
67.0%
Common4002
33.0%

Most frequent character per script

Common
ValueCountFrequency (%)
/966
24.1%
'552
13.8%
.414
10.3%
2300
 
7.5%
:276
 
6.9%
207
 
5.2%
7200
 
5.0%
3154
 
3.8%
8150
 
3.7%
9144
 
3.6%
Other values (9)639
16.0%
Latin
ValueCountFrequency (%)
a828
 
10.2%
t759
 
9.3%
m690
 
8.5%
i690
 
8.5%
s621
 
7.6%
e552
 
6.8%
o483
 
5.9%
p483
 
5.9%
g414
 
5.1%
c414
 
5.1%
Other values (9)2208
27.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII12144
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/966
 
8.0%
a828
 
6.8%
t759
 
6.2%
m690
 
5.7%
i690
 
5.7%
s621
 
5.1%
e552
 
4.5%
'552
 
4.5%
o483
 
4.0%
p483
 
4.0%
Other values (28)5520
45.5%

summary
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct54
Distinct (%)41.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
nan
78 
<p>Donald and Daisy's little lie becomes a big problem when they try to get out of a group date with Mickey and Minnie.</p>
 
1
<p>An unexpected savior protects the children from harm as Hyun-su, together with Yoon Ji Soo and Jung Jae Hun, tries to bring them to safety.</p><p><br /> </p>
 
1
<p>Critical information about the monsters is made public. When residents are split on what to do with Hyun Soo, Lee Eun Hyuk suggests they hold a vote.</p><p><br /> </p>
 
1
<p>Tasked to carry out dangerous missions, Hyun Soo heads back to retrieve Han Du Shik. Sang Wook stops at nothing to finish what he started.</p><p><br /> </p>
 
1
Other values (49)
49 

Length

Max length665
Median length3
Mean length109.778626
Min length3

Characters and Unicode

Total characters14381
Distinct characters77
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)40.5%

Sample

1st rownan
2nd rownan
3rd rownan
4th rownan
5th rownan

Common Values

ValueCountFrequency (%)
nan78
59.5%
<p>Donald and Daisy's little lie becomes a big problem when they try to get out of a group date with Mickey and Minnie.</p>1
 
0.8%
<p>An unexpected savior protects the children from harm as Hyun-su, together with Yoon Ji Soo and Jung Jae Hun, tries to bring them to safety.</p><p><br /> </p>1
 
0.8%
<p>Critical information about the monsters is made public. When residents are split on what to do with Hyun Soo, Lee Eun Hyuk suggests they hold a vote.</p><p><br /> </p>1
 
0.8%
<p>Tasked to carry out dangerous missions, Hyun Soo heads back to retrieve Han Du Shik. Sang Wook stops at nothing to finish what he started.</p><p><br /> </p>1
 
0.8%
<p>An Sun Young confronts the greatest monster in her life. Leaving the building, Seo Yi Kyung heads to her fiancé's office in search of answers.</p><p><br /> </p>1
 
0.8%
<p>Hyun Soo saves the others from a deadly attack. Running out of necessities, Eun Hyuk announces a plan to venture outside for resources.</p><p><br /> </p>1
 
0.8%
<p>Having little options in her state of being, Ji Soo agrees to take a big risk. Yi Kyung returns to Green Home just in time.</p><p><br /> </p>1
 
0.8%
<p>When a team of outlaws take over the building, the residents are shown how humans can be even more barbaric than the monsters.</p><p><br /> </p>1
 
0.8%
<p>A military leaflet promises a route to safety, but the group is reluctant to trust it. Hyun Soo is exposed to a new perspective on his condition.</p>1
 
0.8%
Other values (44)44
33.6%

Length

2022-05-09T21:16:53.273160image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the123
 
5.1%
to97
 
4.0%
a83
 
3.4%
nan78
 
3.2%
and62
 
2.5%
of52
 
2.1%
in31
 
1.3%
her30
 
1.2%
their28
 
1.1%
with25
 
1.0%
Other values (963)1826
75.0%

Most occurring characters

ValueCountFrequency (%)
2271
15.8%
e1322
 
9.2%
a1003
 
7.0%
n988
 
6.9%
t949
 
6.6%
i787
 
5.5%
o753
 
5.2%
s734
 
5.1%
r677
 
4.7%
h545
 
3.8%
Other values (67)4352
30.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter10838
75.4%
Space Separator2308
 
16.0%
Uppercase Letter496
 
3.4%
Other Punctuation397
 
2.8%
Math Symbol310
 
2.2%
Decimal Number18
 
0.1%
Dash Punctuation11
 
0.1%
Initial Punctuation1
 
< 0.1%
Close Punctuation1
 
< 0.1%
Open Punctuation1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e1322
12.2%
a1003
 
9.3%
n988
 
9.1%
t949
 
8.8%
i787
 
7.3%
o753
 
6.9%
s734
 
6.8%
r677
 
6.2%
h545
 
5.0%
l388
 
3.6%
Other values (19)2692
24.8%
Uppercase Letter
ValueCountFrequency (%)
S44
 
8.9%
I34
 
6.9%
J33
 
6.7%
T32
 
6.5%
R30
 
6.0%
A28
 
5.6%
C26
 
5.2%
P24
 
4.8%
K23
 
4.6%
V20
 
4.0%
Other values (14)202
40.7%
Other Punctuation
ValueCountFrequency (%)
.144
36.3%
,109
27.5%
/88
22.2%
'43
 
10.8%
?6
 
1.5%
"4
 
1.0%
;1
 
0.3%
#1
 
0.3%
:1
 
0.3%
Decimal Number
ValueCountFrequency (%)
18
44.4%
93
 
16.7%
22
 
11.1%
02
 
11.1%
81
 
5.6%
61
 
5.6%
41
 
5.6%
Space Separator
ValueCountFrequency (%)
2271
98.4%
 37
 
1.6%
Math Symbol
ValueCountFrequency (%)
>155
50.0%
<155
50.0%
Dash Punctuation
ValueCountFrequency (%)
-11
100.0%
Initial Punctuation
ValueCountFrequency (%)
1
100.0%
Close Punctuation
ValueCountFrequency (%)
)1
100.0%
Open Punctuation
ValueCountFrequency (%)
(1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin11334
78.8%
Common3047
 
21.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e1322
11.7%
a1003
 
8.8%
n988
 
8.7%
t949
 
8.4%
i787
 
6.9%
o753
 
6.6%
s734
 
6.5%
r677
 
6.0%
h545
 
4.8%
l388
 
3.4%
Other values (43)3188
28.1%
Common
ValueCountFrequency (%)
2271
74.5%
>155
 
5.1%
<155
 
5.1%
.144
 
4.7%
,109
 
3.6%
/88
 
2.9%
'43
 
1.4%
 37
 
1.2%
-11
 
0.4%
18
 
0.3%
Other values (14)26
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII14330
99.6%
None50
 
0.3%
Punctuation1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2271
15.8%
e1322
 
9.2%
a1003
 
7.0%
n988
 
6.9%
t949
 
6.6%
i787
 
5.5%
o753
 
5.3%
s734
 
5.1%
r677
 
4.7%
h545
 
3.8%
Other values (62)4301
30.0%
None
ValueCountFrequency (%)
 37
74.0%
ó6
 
12.0%
í6
 
12.0%
é1
 
2.0%
Punctuation
ValueCountFrequency (%)
1
100.0%

_embedded_show_id
Real number (ℝ≥0)

HIGH CORRELATION

Distinct65
Distinct (%)49.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46943.9313
Minimum7847
Maximum57029
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2022-05-09T21:16:53.516070image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum7847
5-th percentile20884.5
Q144117
median51136
Q352582
95-th percentile54889
Maximum57029
Range49182
Interquartile range (IQR)8465

Descriptive statistics

Standard deviation9556.221795
Coefficient of variation (CV)0.2035667131
Kurtosis5.883576359
Mean46943.9313
Median Absolute Deviation (MAD)2623
Skewness-2.358755978
Sum6149655
Variance91321375
MonotonicityNot monotonic
2022-05-09T21:16:53.736305image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5259312
 
9.2%
4411710
 
7.6%
4657010
 
7.6%
525828
 
6.1%
518366
 
4.6%
414896
 
4.6%
410675
 
3.8%
570294
 
3.1%
524514
 
3.1%
547622
 
1.5%
Other values (55)64
48.9%
ValueCountFrequency (%)
78471
0.8%
115022
1.5%
152502
1.5%
191111
0.8%
207341
0.8%
210351
0.8%
306061
0.8%
354201
0.8%
381711
0.8%
387321
0.8%
ValueCountFrequency (%)
570294
 
3.1%
564331
 
0.8%
550191
 
0.8%
550161
 
0.8%
547622
 
1.5%
537591
 
0.8%
530721
 
0.8%
528001
 
0.8%
527822
 
1.5%
5259312
9.2%

_embedded_show_url
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct65
Distinct (%)49.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
https://www.tvmaze.com/shows/52593/black-widows
12 
https://www.tvmaze.com/shows/44117/red
10 
https://www.tvmaze.com/shows/46570/sweet-home
10 
https://www.tvmaze.com/shows/52582/taqdeer
 
8
https://www.tvmaze.com/shows/51836/on-pointe
 
6
Other values (60)
85 

Length

Max length70
Median length59
Mean length47.02290076
Min length38

Characters and Unicode

Total characters6160
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)35.1%

Sample

1st rowhttps://www.tvmaze.com/shows/7847/po-sezonu-videodajdzest-seasonvar
2nd rowhttps://www.tvmaze.com/shows/48402/cuma
3rd rowhttps://www.tvmaze.com/shows/48403/to-so-sketci
4th rowhttps://www.tvmaze.com/shows/52520/muzskaa-tema
5th rowhttps://www.tvmaze.com/shows/20734/fox-spirit-matchmaker

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/shows/52593/black-widows12
 
9.2%
https://www.tvmaze.com/shows/44117/red10
 
7.6%
https://www.tvmaze.com/shows/46570/sweet-home10
 
7.6%
https://www.tvmaze.com/shows/52582/taqdeer8
 
6.1%
https://www.tvmaze.com/shows/51836/on-pointe6
 
4.6%
https://www.tvmaze.com/shows/41489/hjem-til-jul6
 
4.6%
https://www.tvmaze.com/shows/41067/el-cid5
 
3.8%
https://www.tvmaze.com/shows/57029/bablo4
 
3.1%
https://www.tvmaze.com/shows/52451/the-burning-river4
 
3.1%
https://www.tvmaze.com/shows/54762/youths-in-the-breeze2
 
1.5%
Other values (55)64
48.9%

Length

2022-05-09T21:16:53.928506image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/shows/52593/black-widows12
 
9.2%
https://www.tvmaze.com/shows/46570/sweet-home10
 
7.6%
https://www.tvmaze.com/shows/44117/red10
 
7.6%
https://www.tvmaze.com/shows/52582/taqdeer8
 
6.1%
https://www.tvmaze.com/shows/51836/on-pointe6
 
4.6%
https://www.tvmaze.com/shows/41489/hjem-til-jul6
 
4.6%
https://www.tvmaze.com/shows/41067/el-cid5
 
3.8%
https://www.tvmaze.com/shows/57029/bablo4
 
3.1%
https://www.tvmaze.com/shows/52451/the-burning-river4
 
3.1%
https://www.tvmaze.com/shows/52571/lassemajas-detektivbyra2
 
1.5%
Other values (55)64
48.9%

Most occurring characters

ValueCountFrequency (%)
/655
 
10.6%
w576
 
9.4%
t484
 
7.9%
s475
 
7.7%
o374
 
6.1%
e322
 
5.2%
h321
 
5.2%
m319
 
5.2%
.262
 
4.3%
a215
 
3.5%
Other values (30)2157
35.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4297
69.8%
Other Punctuation1048
 
17.0%
Decimal Number654
 
10.6%
Dash Punctuation161
 
2.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w576
13.4%
t484
11.3%
s475
11.1%
o374
8.7%
e322
 
7.5%
h321
 
7.5%
m319
 
7.4%
a215
 
5.0%
c170
 
4.0%
p151
 
3.5%
Other values (16)890
20.7%
Decimal Number
ValueCountFrequency (%)
5135
20.6%
189
13.6%
489
13.6%
277
11.8%
752
 
8.0%
050
 
7.6%
342
 
6.4%
942
 
6.4%
642
 
6.4%
836
 
5.5%
Other Punctuation
ValueCountFrequency (%)
/655
62.5%
.262
 
25.0%
:131
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-161
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4297
69.8%
Common1863
30.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
w576
13.4%
t484
11.3%
s475
11.1%
o374
8.7%
e322
 
7.5%
h321
 
7.5%
m319
 
7.4%
a215
 
5.0%
c170
 
4.0%
p151
 
3.5%
Other values (16)890
20.7%
Common
ValueCountFrequency (%)
/655
35.2%
.262
 
14.1%
-161
 
8.6%
5135
 
7.2%
:131
 
7.0%
189
 
4.8%
489
 
4.8%
277
 
4.1%
752
 
2.8%
050
 
2.7%
Other values (4)162
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII6160
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/655
 
10.6%
w576
 
9.4%
t484
 
7.9%
s475
 
7.7%
o374
 
6.1%
e322
 
5.2%
h321
 
5.2%
m319
 
5.2%
.262
 
4.3%
a215
 
3.5%
Other values (30)2157
35.0%

_embedded_show_name
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct65
Distinct (%)49.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Black Widows
12 
RED
10 
Sweet Home
10 
Taqdeer
 
8
On Pointe
 
6
Other values (60)
85 

Length

Max length35
Median length24
Mean length12.1221374
Min length3

Characters and Unicode

Total characters1588
Distinct characters91
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)35.1%

Sample

1st rowПо сезону. Видеодайджест Seasonvar
2nd rowЧума!
3rd rowТо шо скетчи
4th rowМужская тема
5th rowFox Spirit Matchmaker

Common Values

ValueCountFrequency (%)
Black Widows12
 
9.2%
RED10
 
7.6%
Sweet Home10
 
7.6%
Taqdeer8
 
6.1%
On Pointe6
 
4.6%
Hjem til jul6
 
4.6%
El Cid5
 
3.8%
Bablo4
 
3.1%
The Burning River4
 
3.1%
Youths in the Breeze2
 
1.5%
Other values (55)64
48.9%

Length

2022-05-09T21:16:54.069505image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the16
 
5.5%
black12
 
4.1%
widows12
 
4.1%
red11
 
3.8%
home11
 
3.8%
sweet10
 
3.4%
taqdeer8
 
2.7%
til7
 
2.4%
on6
 
2.1%
pointe6
 
2.1%
Other values (132)192
66.0%

Most occurring characters

ValueCountFrequency (%)
e168
 
10.6%
160
 
10.1%
o91
 
5.7%
i89
 
5.6%
a73
 
4.6%
r68
 
4.3%
n67
 
4.2%
l63
 
4.0%
t59
 
3.7%
s55
 
3.5%
Other values (81)695
43.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1138
71.7%
Uppercase Letter278
 
17.5%
Space Separator160
 
10.1%
Other Punctuation11
 
0.7%
Dash Punctuation1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e168
14.8%
o91
 
8.0%
i89
 
7.8%
a73
 
6.4%
r68
 
6.0%
n67
 
5.9%
l63
 
5.5%
t59
 
5.2%
s55
 
4.8%
d44
 
3.9%
Other values (42)361
31.7%
Uppercase Letter
ValueCountFrequency (%)
T27
 
9.7%
W25
 
9.0%
B23
 
8.3%
H23
 
8.3%
S22
 
7.9%
D20
 
7.2%
R19
 
6.8%
M17
 
6.1%
E17
 
6.1%
C12
 
4.3%
Other values (23)73
26.3%
Other Punctuation
ValueCountFrequency (%)
:4
36.4%
!3
27.3%
.3
27.3%
?1
 
9.1%
Space Separator
ValueCountFrequency (%)
160
100.0%
Dash Punctuation
ValueCountFrequency (%)
-1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1354
85.3%
Common172
 
10.8%
Cyrillic62
 
3.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e168
 
12.4%
o91
 
6.7%
i89
 
6.6%
a73
 
5.4%
r68
 
5.0%
n67
 
4.9%
l63
 
4.7%
t59
 
4.4%
s55
 
4.1%
d44
 
3.2%
Other values (46)577
42.6%
Cyrillic
ValueCountFrequency (%)
о8
 
12.9%
а5
 
8.1%
е5
 
8.1%
д4
 
6.5%
т4
 
6.5%
с4
 
6.5%
у3
 
4.8%
и3
 
4.8%
ж2
 
3.2%
к2
 
3.2%
Other values (19)22
35.5%
Common
ValueCountFrequency (%)
160
93.0%
:4
 
2.3%
!3
 
1.7%
.3
 
1.7%
-1
 
0.6%
?1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII1519
95.7%
Cyrillic62
 
3.9%
None7
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e168
 
11.1%
160
 
10.5%
o91
 
6.0%
i89
 
5.9%
a73
 
4.8%
r68
 
4.5%
n67
 
4.4%
l63
 
4.1%
t59
 
3.9%
s55
 
3.6%
Other values (48)626
41.2%
Cyrillic
ValueCountFrequency (%)
о8
 
12.9%
а5
 
8.1%
е5
 
8.1%
д4
 
6.5%
т4
 
6.5%
с4
 
6.5%
у3
 
4.8%
и3
 
4.8%
ж2
 
3.2%
к2
 
3.2%
Other values (19)22
35.5%
None
ValueCountFrequency (%)
ø3
42.9%
å2
28.6%
é1
 
14.3%
ä1
 
14.3%

_embedded_show_type
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct7
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Scripted
94 
Documentary
13 
Animation
10 
Talk Show
 
6
Reality
 
4
Other values (2)
 
4

Length

Max length11
Median length8
Mean length8.312977099
Min length4

Characters and Unicode

Total characters1089
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowTalk Show
2nd rowScripted
3rd rowVariety
4th rowTalk Show
5th rowAnimation

Common Values

ValueCountFrequency (%)
Scripted94
71.8%
Documentary13
 
9.9%
Animation10
 
7.6%
Talk Show6
 
4.6%
Reality4
 
3.1%
Variety2
 
1.5%
News2
 
1.5%

Length

2022-05-09T21:16:54.210338image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:16:54.336291image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
scripted94
68.6%
documentary13
 
9.5%
animation10
 
7.3%
talk6
 
4.4%
show6
 
4.4%
reality4
 
2.9%
variety2
 
1.5%
news2
 
1.5%

Most occurring characters

ValueCountFrequency (%)
t123
11.3%
i120
11.0%
e115
10.6%
r109
10.0%
c107
9.8%
S100
9.2%
p94
8.6%
d94
8.6%
a35
 
3.2%
n33
 
3.0%
Other values (16)159
14.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter946
86.9%
Uppercase Letter137
 
12.6%
Space Separator6
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t123
13.0%
i120
12.7%
e115
12.2%
r109
11.5%
c107
11.3%
p94
9.9%
d94
9.9%
a35
 
3.7%
n33
 
3.5%
o29
 
3.1%
Other values (8)87
9.2%
Uppercase Letter
ValueCountFrequency (%)
S100
73.0%
D13
 
9.5%
A10
 
7.3%
T6
 
4.4%
R4
 
2.9%
V2
 
1.5%
N2
 
1.5%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1083
99.4%
Common6
 
0.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t123
11.4%
i120
11.1%
e115
10.6%
r109
10.1%
c107
9.9%
S100
9.2%
p94
8.7%
d94
8.7%
a35
 
3.2%
n33
 
3.0%
Other values (15)153
14.1%
Common
ValueCountFrequency (%)
6
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1089
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t123
11.3%
i120
11.0%
e115
10.6%
r109
10.0%
c107
9.8%
S100
9.2%
p94
8.6%
d94
8.6%
a35
 
3.2%
n33
 
3.0%
Other values (16)159
14.6%

_embedded_show_language
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct16
Distinct (%)12.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
English
20 
Norwegian
19 
Chinese
18 
Korean
17 
Hindi
13 
Other values (11)
44 

Length

Max length10
Median length9
Mean length7.114503817
Min length4

Characters and Unicode

Total characters932
Distinct characters32
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)2.3%

Sample

1st rowRussian
2nd rowRussian
3rd rowRussian
4th rowRussian
5th rowChinese

Common Values

ValueCountFrequency (%)
English20
15.3%
Norwegian19
14.5%
Chinese18
13.7%
Korean17
13.0%
Hindi13
9.9%
Portuguese11
8.4%
Bengali8
 
6.1%
Spanish8
 
6.1%
Russian6
 
4.6%
Dutch2
 
1.5%
Other values (6)9
6.9%

Length

2022-05-09T21:16:54.465443image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
english20
15.3%
norwegian19
14.5%
chinese18
13.7%
korean17
13.0%
hindi13
9.9%
portuguese11
8.4%
bengali8
 
6.1%
spanish8
 
6.1%
russian6
 
4.6%
dutch2
 
1.5%
Other values (6)9
6.9%

Most occurring characters

ValueCountFrequency (%)
n110
11.8%
i110
11.8%
e105
11.3%
s72
 
7.7%
a67
 
7.2%
g62
 
6.7%
h53
 
5.7%
o49
 
5.3%
r49
 
5.3%
l31
 
3.3%
Other values (22)224
24.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter801
85.9%
Uppercase Letter131
 
14.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n110
13.7%
i110
13.7%
e105
13.1%
s72
9.0%
a67
8.4%
g62
7.7%
h53
6.6%
o49
6.1%
r49
6.1%
l31
 
3.9%
Other values (9)93
11.6%
Uppercase Letter
ValueCountFrequency (%)
E20
15.3%
N19
14.5%
C18
13.7%
K17
13.0%
H13
9.9%
P11
8.4%
S10
7.6%
B8
 
6.1%
R6
 
4.6%
T5
 
3.8%
Other values (3)4
 
3.1%

Most occurring scripts

ValueCountFrequency (%)
Latin932
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n110
11.8%
i110
11.8%
e105
11.3%
s72
 
7.7%
a67
 
7.2%
g62
 
6.7%
h53
 
5.7%
o49
 
5.3%
r49
 
5.3%
l31
 
3.3%
Other values (22)224
24.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII932
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n110
11.8%
i110
11.8%
e105
11.3%
s72
 
7.7%
a67
 
7.2%
g62
 
6.7%
h53
 
5.7%
o49
 
5.3%
r49
 
5.3%
l31
 
3.3%
Other values (22)224
24.0%

_embedded_show_genres
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct34
Distinct (%)26.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
[]
18 
['Drama', 'Romance']
16 
['Drama', 'Crime', 'Mystery']
12 
['Drama', 'Comedy', 'Romance']
11 
['Horror', 'Science-Fiction', 'Thriller']
10 
Other values (29)
64 

Length

Max length46
Median length35
Mean length23.14503817
Min length2

Characters and Unicode

Total characters3032
Distinct characters33
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)12.2%

Sample

1st row[]
2nd row['Comedy']
3rd row['Comedy']
4th row[]
5th row['Comedy', 'Anime', 'Fantasy', 'Romance']

Common Values

ValueCountFrequency (%)
[]18
13.7%
['Drama', 'Romance']16
12.2%
['Drama', 'Crime', 'Mystery']12
 
9.2%
['Drama', 'Comedy', 'Romance']11
 
8.4%
['Horror', 'Science-Fiction', 'Thriller']10
 
7.6%
['Comedy']9
 
6.9%
['Crime', 'Thriller', 'Mystery']8
 
6.1%
['Comedy', 'Children']6
 
4.6%
['Drama', 'Adventure', 'History']5
 
3.8%
['Drama', 'Action', 'Thriller']4
 
3.1%
Other values (24)32
24.4%

Length

2022-05-09T21:16:54.612808image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
drama65
21.6%
romance33
11.0%
comedy32
10.6%
crime25
 
8.3%
thriller23
 
7.6%
mystery22
 
7.3%
18
 
6.0%
horror11
 
3.7%
science-fiction11
 
3.7%
history10
 
3.3%
Other values (10)51
16.9%

Most occurring characters

ValueCountFrequency (%)
'566
18.7%
r224
 
7.4%
e190
 
6.3%
a185
 
6.1%
,170
 
5.6%
170
 
5.6%
m166
 
5.5%
[131
 
4.3%
]131
 
4.3%
i123
 
4.1%
Other values (23)976
32.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1559
51.4%
Other Punctuation736
24.3%
Uppercase Letter294
 
9.7%
Space Separator170
 
5.6%
Open Punctuation131
 
4.3%
Close Punctuation131
 
4.3%
Dash Punctuation11
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r224
14.4%
e190
12.2%
a185
11.9%
m166
10.6%
i123
7.9%
o121
7.8%
y96
6.2%
n94
6.0%
c79
 
5.1%
t68
 
4.4%
Other values (7)213
13.7%
Uppercase Letter
ValueCountFrequency (%)
C65
22.1%
D65
22.1%
R33
11.2%
M26
 
8.8%
F23
 
7.8%
T23
 
7.8%
A23
 
7.8%
H21
 
7.1%
S14
 
4.8%
W1
 
0.3%
Other Punctuation
ValueCountFrequency (%)
'566
76.9%
,170
 
23.1%
Space Separator
ValueCountFrequency (%)
170
100.0%
Open Punctuation
ValueCountFrequency (%)
[131
100.0%
Close Punctuation
ValueCountFrequency (%)
]131
100.0%
Dash Punctuation
ValueCountFrequency (%)
-11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1853
61.1%
Common1179
38.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
r224
12.1%
e190
 
10.3%
a185
 
10.0%
m166
 
9.0%
i123
 
6.6%
o121
 
6.5%
y96
 
5.2%
n94
 
5.1%
c79
 
4.3%
t68
 
3.7%
Other values (17)507
27.4%
Common
ValueCountFrequency (%)
'566
48.0%
,170
 
14.4%
170
 
14.4%
[131
 
11.1%
]131
 
11.1%
-11
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII3032
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
'566
18.7%
r224
 
7.4%
e190
 
6.3%
a185
 
6.1%
,170
 
5.6%
170
 
5.6%
m166
 
5.5%
[131
 
4.3%
]131
 
4.3%
i123
 
4.1%
Other values (23)976
32.2%

_embedded_show_status
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct3
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Ended
62 
Running
46 
To Be Determined
23 

Length

Max length16
Median length7
Mean length7.633587786
Min length5

Characters and Unicode

Total characters1000
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRunning
2nd rowEnded
3rd rowEnded
4th rowEnded
5th rowRunning

Common Values

ValueCountFrequency (%)
Ended62
47.3%
Running46
35.1%
To Be Determined23
 
17.6%

Length

2022-05-09T21:16:54.706341image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:16:54.916117image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
ended62
35.0%
running46
26.0%
to23
 
13.0%
be23
 
13.0%
determined23
 
13.0%

Most occurring characters

ValueCountFrequency (%)
n223
22.3%
e154
15.4%
d147
14.7%
i69
 
6.9%
E62
 
6.2%
R46
 
4.6%
u46
 
4.6%
g46
 
4.6%
46
 
4.6%
T23
 
2.3%
Other values (6)138
13.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter777
77.7%
Uppercase Letter177
 
17.7%
Space Separator46
 
4.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n223
28.7%
e154
19.8%
d147
18.9%
i69
 
8.9%
u46
 
5.9%
g46
 
5.9%
o23
 
3.0%
t23
 
3.0%
r23
 
3.0%
m23
 
3.0%
Uppercase Letter
ValueCountFrequency (%)
E62
35.0%
R46
26.0%
T23
 
13.0%
B23
 
13.0%
D23
 
13.0%
Space Separator
ValueCountFrequency (%)
46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin954
95.4%
Common46
 
4.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
n223
23.4%
e154
16.1%
d147
15.4%
i69
 
7.2%
E62
 
6.5%
R46
 
4.8%
u46
 
4.8%
g46
 
4.8%
T23
 
2.4%
o23
 
2.4%
Other values (5)115
12.1%
Common
ValueCountFrequency (%)
46
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n223
22.3%
e154
15.4%
d147
14.7%
i69
 
6.9%
E62
 
6.2%
R46
 
4.6%
u46
 
4.6%
g46
 
4.6%
46
 
4.6%
T23
 
2.3%
Other values (6)138
13.8%

_embedded_show_runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct23
Distinct (%)26.7%
Missing45
Missing (%)34.4%
Infinite0
Infinite (%)0.0%
Mean28.48837209
Minimum1
Maximum120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2022-05-09T21:16:55.008754image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8
Q115
median25
Q338.75
95-th percentile50
Maximum120
Range119
Interquartile range (IQR)23.75

Descriptive statistics

Standard deviation20.24424054
Coefficient of variation (CV)0.7106141577
Kurtosis7.97914519
Mean28.48837209
Median Absolute Deviation (MAD)10
Skewness2.18618974
Sum2450
Variance409.829275
MonotonicityNot monotonic
2022-05-09T21:16:55.115899image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
1514
 
10.7%
3512
 
9.2%
4511
 
8.4%
2510
 
7.6%
109
 
6.9%
503
 
2.3%
203
 
2.3%
303
 
2.3%
1202
 
1.5%
72
 
1.5%
Other values (13)17
 
13.0%
(Missing)45
34.4%
ValueCountFrequency (%)
11
 
0.8%
51
 
0.8%
72
 
1.5%
82
 
1.5%
91
 
0.8%
109
6.9%
112
 
1.5%
141
 
0.8%
1514
10.7%
203
 
2.3%
ValueCountFrequency (%)
1202
 
1.5%
602
 
1.5%
503
 
2.3%
481
 
0.8%
4511
8.4%
422
 
1.5%
401
 
0.8%
3512
9.2%
303
 
2.3%
281
 
0.8%

_embedded_show_averageRuntime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct35
Distinct (%)27.1%
Missing2
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean31.47286822
Minimum1
Maximum120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2022-05-09T21:16:55.205399image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8
Q114
median30
Q345
95-th percentile59
Maximum120
Range119
Interquartile range (IQR)31

Descriptive statistics

Standard deviation20.23536412
Coefficient of variation (CV)0.6429462985
Kurtosis3.898512356
Mean31.47286822
Median Absolute Deviation (MAD)15
Skewness1.314816548
Sum4060
Variance409.4699612
MonotonicityNot monotonic
2022-05-09T21:16:55.333356image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
4517
13.0%
1412
 
9.2%
3512
 
9.2%
2510
 
7.6%
5210
 
7.6%
307
 
5.3%
86
 
4.6%
115
 
3.8%
595
 
3.8%
105
 
3.8%
Other values (25)40
30.5%
ValueCountFrequency (%)
11
 
0.8%
52
 
1.5%
61
 
0.8%
72
 
1.5%
86
4.6%
92
 
1.5%
105
3.8%
115
3.8%
122
 
1.5%
1412
9.2%
ValueCountFrequency (%)
1202
 
1.5%
761
 
0.8%
601
 
0.8%
595
 
3.8%
542
 
1.5%
5210
7.6%
503
 
2.3%
481
 
0.8%
461
 
0.8%
4517
13.0%

_embedded_show_premiered
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct52
Distinct (%)39.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2020-12-18
41 
2014-09-27
10 
2020-12-04
2019-12-05
 
6
2020-12-11
 
5
Other values (47)
62 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters1310
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)26.7%

Sample

1st row2015-02-13
2nd row2020-05-29
3rd row2020-05-25
4th row2020-12-17
5th row2015-06-26

Common Values

ValueCountFrequency (%)
2020-12-1841
31.3%
2014-09-2710
 
7.6%
2020-12-047
 
5.3%
2019-12-056
 
4.6%
2020-12-115
 
3.8%
2020-04-144
 
3.1%
2020-12-103
 
2.3%
2020-09-112
 
1.5%
2013-12-242
 
1.5%
2020-12-062
 
1.5%
Other values (42)49
37.4%

Length

2022-05-09T21:16:55.467499image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-1841
31.3%
2014-09-2710
 
7.6%
2020-12-047
 
5.3%
2019-12-056
 
4.6%
2020-12-115
 
3.8%
2020-04-144
 
3.1%
2020-12-103
 
2.3%
2012-01-282
 
1.5%
2020-12-132
 
1.5%
2020-11-192
 
1.5%
Other values (42)49
37.4%

Most occurring characters

ValueCountFrequency (%)
2334
25.5%
0294
22.4%
-262
20.0%
1240
18.3%
856
 
4.3%
436
 
2.7%
933
 
2.5%
720
 
1.5%
517
 
1.3%
311
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number1048
80.0%
Dash Punctuation262
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2334
31.9%
0294
28.1%
1240
22.9%
856
 
5.3%
436
 
3.4%
933
 
3.1%
720
 
1.9%
517
 
1.6%
311
 
1.0%
67
 
0.7%
Dash Punctuation
ValueCountFrequency (%)
-262
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1310
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2334
25.5%
0294
22.4%
-262
20.0%
1240
18.3%
856
 
4.3%
436
 
2.7%
933
 
2.5%
720
 
1.5%
517
 
1.3%
311
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII1310
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2334
25.5%
0294
22.4%
-262
20.0%
1240
18.3%
856
 
4.3%
436
 
2.7%
933
 
2.5%
720
 
1.5%
517
 
1.3%
311
 
0.8%

_embedded_show_ended
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct19
Distinct (%)14.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
nan
69 
2020-12-18
37 
2020-12-25
 
5
2020-12-22
 
2
2021-01-22
 
2
Other values (14)
16 

Length

Max length10
Median length3
Mean length6.312977099
Min length3

Characters and Unicode

Total characters827
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)9.2%

Sample

1st rownan
2nd row2020-12-18
3rd row2021-03-11
4th row2020-12-25
5th rownan

Common Values

ValueCountFrequency (%)
nan69
52.7%
2020-12-1837
28.2%
2020-12-255
 
3.8%
2020-12-222
 
1.5%
2021-01-222
 
1.5%
2021-01-142
 
1.5%
2021-01-042
 
1.5%
2021-02-121
 
0.8%
2020-12-241
 
0.8%
2021-03-121
 
0.8%
Other values (9)9
 
6.9%

Length

2022-05-09T21:16:55.599735image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
nan69
52.7%
2020-12-1837
28.2%
2020-12-255
 
3.8%
2020-12-222
 
1.5%
2021-01-222
 
1.5%
2021-01-142
 
1.5%
2021-01-042
 
1.5%
2021-02-051
 
0.8%
2021-01-051
 
0.8%
2021-01-291
 
0.8%
Other values (9)9
 
6.9%

Most occurring characters

ValueCountFrequency (%)
2189
22.9%
n138
16.7%
0132
16.0%
-124
15.0%
1119
14.4%
a69
 
8.3%
839
 
4.7%
58
 
1.0%
45
 
0.6%
32
 
0.2%
Other values (2)2
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number496
60.0%
Lowercase Letter207
25.0%
Dash Punctuation124
 
15.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2189
38.1%
0132
26.6%
1119
24.0%
839
 
7.9%
58
 
1.6%
45
 
1.0%
32
 
0.4%
61
 
0.2%
91
 
0.2%
Lowercase Letter
ValueCountFrequency (%)
n138
66.7%
a69
33.3%
Dash Punctuation
ValueCountFrequency (%)
-124
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common620
75.0%
Latin207
 
25.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2189
30.5%
0132
21.3%
-124
20.0%
1119
19.2%
839
 
6.3%
58
 
1.3%
45
 
0.8%
32
 
0.3%
61
 
0.2%
91
 
0.2%
Latin
ValueCountFrequency (%)
n138
66.7%
a69
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII827
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2189
22.9%
n138
16.7%
0132
16.0%
-124
15.0%
1119
14.4%
a69
 
8.3%
839
 
4.7%
58
 
1.0%
45
 
0.6%
32
 
0.2%
Other values (2)2
 
0.2%

_embedded_show_officialSite
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct60
Distinct (%)45.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
nan
22 
https://www.zee5.com/global/zee5originals/details/black-widows/0-6-3029
12 
https://www.netflix.com/title/81061734
10 
https://www.hoichoi.tv/webseries/taqdeer
https://www.netflix.com/title/81083590
 
6
Other values (55)
73 

Length

Max length250
Median length88
Mean length45.9389313
Min length3

Characters and Unicode

Total characters6018
Distinct characters73
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)33.6%

Sample

1st rowhttp://seasonvar.ru/serial-11488-Po_sezonu_Videodajdzhest_Seasonvar.html
2nd rowhttps://www.ivi.ru/watch/chuma-2020
3rd rowhttps://premier.one/show/to-sho-sketchi
4th rowhttps://www.ivi.ru/watch/muzhskaya-tema
5th rowhttp://www.bilibili.com/bangumi/%E7%8B%90%E5%A6%96%E5%B0%8F%E7%BA%A2%E5%A8%98/

Common Values

ValueCountFrequency (%)
nan22
 
16.8%
https://www.zee5.com/global/zee5originals/details/black-widows/0-6-302912
 
9.2%
https://www.netflix.com/title/8106173410
 
7.6%
https://www.hoichoi.tv/webseries/taqdeer8
 
6.1%
https://www.netflix.com/title/810835906
 
4.6%
https://www.amazon.com/dp/B08NSTBD1Q/5
 
3.8%
https://v.youku.com/v_show/id_XNDk1MzY2NzgwNA==.html?spm=a2h0c.8166622.PhoneSokuProgram_1.dtitle&s=aaed627feea749d7a99d4
 
3.1%
https://tv.nrk.no/serie/bablo4
 
3.1%
https://www.iq.com/play/1n40eysnffc2
 
1.5%
https://www.viki.com/tv/37486c-wish-you2
 
1.5%
Other values (50)56
42.7%

Length

2022-05-09T21:16:55.778608image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
nan22
 
16.8%
https://www.zee5.com/global/zee5originals/details/black-widows/0-6-302912
 
9.2%
https://www.netflix.com/title/8106173410
 
7.6%
https://www.hoichoi.tv/webseries/taqdeer8
 
6.1%
https://www.netflix.com/title/810835906
 
4.6%
https://www.amazon.com/dp/b08nstbd1q5
 
3.8%
https://v.youku.com/v_show/id_xndk1mzy2nzgwna==.html?spm=a2h0c.8166622.phonesokuprogram_1.dtitle&s=aaed627feea749d7a99d4
 
3.1%
https://tv.nrk.no/serie/bablo4
 
3.1%
https://www.tytnetwork.com2
 
1.5%
https://v.youku.com/v_show/id_xndk4otuxmzg1mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef2
 
1.5%
Other values (50)56
42.7%

Most occurring characters

ValueCountFrequency (%)
/493
 
8.2%
t415
 
6.9%
e325
 
5.4%
w309
 
5.1%
s283
 
4.7%
o262
 
4.4%
.241
 
4.0%
i236
 
3.9%
a216
 
3.6%
l198
 
3.3%
Other values (63)3040
50.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3891
64.7%
Other Punctuation916
 
15.2%
Decimal Number764
 
12.7%
Uppercase Letter286
 
4.8%
Dash Punctuation91
 
1.5%
Math Symbol40
 
0.7%
Connector Punctuation30
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t415
 
10.7%
e325
 
8.4%
w309
 
7.9%
s283
 
7.3%
o262
 
6.7%
i236
 
6.1%
a216
 
5.6%
l198
 
5.1%
h197
 
5.1%
n160
 
4.1%
Other values (16)1290
33.2%
Uppercase Letter
ValueCountFrequency (%)
N27
 
9.4%
D22
 
7.7%
B22
 
7.7%
S21
 
7.3%
A18
 
6.3%
P18
 
6.3%
E17
 
5.9%
Q12
 
4.2%
C12
 
4.2%
T12
 
4.2%
Other values (16)105
36.7%
Decimal Number
ValueCountFrequency (%)
1117
15.3%
0103
13.5%
676
9.9%
273
9.6%
571
9.3%
371
9.3%
470
9.2%
867
8.8%
961
8.0%
755
7.2%
Other Punctuation
ValueCountFrequency (%)
/493
53.8%
.241
26.3%
:127
 
13.9%
%30
 
3.3%
?14
 
1.5%
&11
 
1.2%
Math Symbol
ValueCountFrequency (%)
=37
92.5%
+2
 
5.0%
~1
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
-91
100.0%
Connector Punctuation
ValueCountFrequency (%)
_30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4177
69.4%
Common1841
30.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t415
 
9.9%
e325
 
7.8%
w309
 
7.4%
s283
 
6.8%
o262
 
6.3%
i236
 
5.6%
a216
 
5.2%
l198
 
4.7%
h197
 
4.7%
n160
 
3.8%
Other values (42)1576
37.7%
Common
ValueCountFrequency (%)
/493
26.8%
.241
13.1%
:127
 
6.9%
1117
 
6.4%
0103
 
5.6%
-91
 
4.9%
676
 
4.1%
273
 
4.0%
571
 
3.9%
371
 
3.9%
Other values (11)378
20.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII6018
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/493
 
8.2%
t415
 
6.9%
e325
 
5.4%
w309
 
5.1%
s283
 
4.7%
o262
 
4.4%
.241
 
4.0%
i236
 
3.9%
a216
 
3.6%
l198
 
3.3%
Other values (63)3040
50.5%

_embedded_show_weight
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct41
Distinct (%)31.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.74045802
Minimum2
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2022-05-09T21:16:55.982282image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3
Q117
median27
Q374
95-th percentile93
Maximum100
Range98
Interquartile range (IQR)57

Descriptive statistics

Standard deviation31.04378738
Coefficient of variation (CV)0.7619891601
Kurtosis-1.229358972
Mean40.74045802
Median Absolute Deviation (MAD)12
Skewness0.5776915855
Sum5337
Variance963.7167352
MonotonicityNot monotonic
2022-05-09T21:16:56.201682image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
1818
13.7%
9315
 
11.5%
311
 
8.4%
1610
 
7.6%
248
 
6.1%
828
 
6.1%
746
 
4.6%
175
 
3.8%
304
 
3.1%
154
 
3.1%
Other values (31)42
32.1%
ValueCountFrequency (%)
21
 
0.8%
311
8.4%
51
 
0.8%
71
 
0.8%
101
 
0.8%
141
 
0.8%
154
 
3.1%
1610
7.6%
175
 
3.8%
1818
13.7%
ValueCountFrequency (%)
1001
 
0.8%
9315
11.5%
881
 
0.8%
828
6.1%
792
 
1.5%
781
 
0.8%
746
 
4.6%
721
 
0.8%
711
 
0.8%
671
 
0.8%

_embedded_show_dvdCountry
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
nan
131 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters393
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rownan
2nd rownan
3rd rownan
4th rownan
5th rownan

Common Values

ValueCountFrequency (%)
nan131
100.0%

Length

2022-05-09T21:16:56.369768image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:16:56.519566image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
nan131
100.0%

Most occurring characters

ValueCountFrequency (%)
n262
66.7%
a131
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter393
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n262
66.7%
a131
33.3%

Most occurring scripts

ValueCountFrequency (%)
Latin393
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n262
66.7%
a131
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII393
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n262
66.7%
a131
33.3%

_embedded_show_summary
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct62
Distinct (%)47.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<p>Veera, Jayati and Kavita, tired of abusive and unloving husbands, plan and execute the murder of their husbands in what they make look like a boat accident. It was an almost perfect plan, as the boat blew up mid sea, when the three couples had gone for a quick vacation, in what looked like a simple boating accident. It's a secret the three women share, a secret that will help them move on from the drudgery of their unhappy lives. How they get out and save themselves is what forms the spine of the series.</p>
12 
<p>A web-series that tells the story of Mel Béart and Liz Malmo, two actresses who meet while shooting a short film and end up taking to their real lives the romantic relationship that they portray in fiction as Scarlet and Simone.</p>
10 
<p>Adapted from a popular webtoon of the same name, <b>Sweet Home</b> is a VFX/SFX filled thriller based on the unique world in which people turn into monsters that reflect their internal desires. Cha Hyun Soo, a reclusive high school student who moves into a new apartment called Green Home after a personal tragedy, faces a series of life changing situations that brings him out to the world to save others. </p>
10 
<p>Freezer van driver Taqdeer spirals into a dark game of destiny after he finds the dead body of an unclaimed woman in his truck.</p>
 
8
<p>Johanne finds herself at 30 years old to be the only one among friends and family without a partner. The constant comments on her single life and society's expectations of the perfect family Christmas finally gets to her. Johanne starts a 24 day hunt for a partner to bring home for Christmas.</p>
 
6
Other values (57)
85 

Length

Max length1360
Median length705
Mean length387.2366412
Min length3

Characters and Unicode

Total characters50728
Distinct characters96
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)32.1%

Sample

1st row<p>Weekly videodaydzhest on site seasonvar.ru and creative team viruseproject.tv. In ten minutes, we talk about the most important events of the past week: look down on the set is not yet published projects, sharing the secrets of private life actors consider the prospects for the development of genres and discuss news TV industry! In videodaydzheste you will find only reliable information from Russian and foreign publications, as well as take part in choosing the best show of the month! Our weekly news videodaydzhest will suit every viewer, so gather good company with family and friends, as well as stock up on popcorn - these ten minutes you shock, delight and inform the latest news about your favorite TV projects!</p>
2nd row<p><b>Plague</b> – a Comedy project about how hard it is to survive in the middle ages during the plague. This is a story about the residents of the fictional town of Hamburg, locked in a castle under quarantine. Also locked up in the castle is the Messenger William, who, in fact, brought the news of the plague.</p>
3rd row<p>"To sho sketches" is an entertaining and unknowable show from the team of "Lena Kuka", in which there is no plot, logic, morality, and even more meaning. So turn off your brain and enjoy!</p>
4th row<p><b>Мужская тема</b> is a symbiosis of talk shows and modern podcasts, where male celebrities answer questions that concern people in the XXI century. Bright representatives of show business, theater, pop, cinema, sports, as well as Internet stars meet in the barbershop. Here, on male territory, they can openly discuss a variety of topics, sometimes seriously, and sometimes with humor. This is a chance to see the idol in a confidential communication without notes, compare his opinion with your own and hear what men really talk about when there is not a single girl around.</p>
5th row<p>Buy UCO from childhood grew up in the clan, Ichigo, but their "care" was for him a living Hell. Constant bullying, stealing the Goodies, without which Ycu can not live, and even eternal persecution, from the fair sex turned him into a goner cheapskate who wants to take revenge on his tormentors. But revenge is sweet and the path to it is thorny and to accomplish, UCU need to marry a girl Yes, as soon as possible. But when the heroes just happen? Never! And meeting with the small and the big-eared Fox Susan su su did not just destroy his plans, but starts spinning the wheel of fate that was waiting in the wings for hundreds of years!</p>

Common Values

ValueCountFrequency (%)
<p>Veera, Jayati and Kavita, tired of abusive and unloving husbands, plan and execute the murder of their husbands in what they make look like a boat accident. It was an almost perfect plan, as the boat blew up mid sea, when the three couples had gone for a quick vacation, in what looked like a simple boating accident. It's a secret the three women share, a secret that will help them move on from the drudgery of their unhappy lives. How they get out and save themselves is what forms the spine of the series.</p>12
 
9.2%
<p>A web-series that tells the story of Mel Béart and Liz Malmo, two actresses who meet while shooting a short film and end up taking to their real lives the romantic relationship that they portray in fiction as Scarlet and Simone.</p>10
 
7.6%
<p>Adapted from a popular webtoon of the same name, <b>Sweet Home</b> is a VFX/SFX filled thriller based on the unique world in which people turn into monsters that reflect their internal desires. Cha Hyun Soo, a reclusive high school student who moves into a new apartment called Green Home after a personal tragedy, faces a series of life changing situations that brings him out to the world to save others. </p>10
 
7.6%
<p>Freezer van driver Taqdeer spirals into a dark game of destiny after he finds the dead body of an unclaimed woman in his truck.</p>8
 
6.1%
<p>Johanne finds herself at 30 years old to be the only one among friends and family without a partner. The constant comments on her single life and society's expectations of the perfect family Christmas finally gets to her. Johanne starts a 24 day hunt for a partner to bring home for Christmas.</p>6
 
4.6%
<p><b>On Pointe</b> captures a season in the School of American Ballet (SAB) in New York City. Featuring unprecedented access to the famous ballet institution, the series follows the lives of the students ages 8 to 18 pursuing their dreams to become ballet dancers. While older students from all over the country rigorously train for professional careers, younger students from New York City are put through their paces as they rehearse and perform in New York City Ballet's holiday classic "George Balanchine's The Nutcracker" onstage at Lincoln Center.</p>6
 
4.6%
<p><b>El Cid</b> retells from a contemporary perspective the story of the most famous Spaniard in history, a man trapped between two worlds and two cultures. A nobleman, a hero, a mercenary, a vassal, but also a man who could have been king. El Cid was centuries ahead of his time and became transcended by his own legend.</p>5
 
3.8%
<p>Welcome to <b>Bablo</b>, the world's best library!</p>4
 
3.1%
<p>Two boggling mysteries have occured in a small town in Xinan. A female police captain joins hands with a young detective to conduct an investigation. Although a clear motive can be seen, the two discover a series of unknown secrets.</p><p>One case involves a late-night ride hailed through an online platform that goes terribly wrong. As more and more clues resurface, the cases in the hands of the police hands become complicated and entangled. In a desperate attempt to find the real culprit, events closely link the past, present and future of the small town.</p>4
 
3.1%
nan4
 
3.1%
Other values (52)62
47.3%

Length

2022-05-09T21:16:56.692601image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the538
 
6.2%
a361
 
4.1%
and286
 
3.3%
of275
 
3.2%
to200
 
2.3%
in181
 
2.1%
that102
 
1.2%
their95
 
1.1%
they73
 
0.8%
is68
 
0.8%
Other values (1656)6539
75.0%

Most occurring characters

ValueCountFrequency (%)
8569
16.9%
e4892
 
9.6%
t3465
 
6.8%
a3215
 
6.3%
o2973
 
5.9%
n2801
 
5.5%
i2573
 
5.1%
s2476
 
4.9%
r2330
 
4.6%
h2115
 
4.2%
Other values (86)15319
30.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter38532
76.0%
Space Separator8592
 
16.9%
Uppercase Letter1321
 
2.6%
Other Punctuation1288
 
2.5%
Math Symbol796
 
1.6%
Decimal Number73
 
0.1%
Dash Punctuation64
 
0.1%
Format24
 
< 0.1%
Close Punctuation19
 
< 0.1%
Open Punctuation19
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e4892
12.7%
t3465
 
9.0%
a3215
 
8.3%
o2973
 
7.7%
n2801
 
7.3%
i2573
 
6.7%
s2476
 
6.4%
r2330
 
6.0%
h2115
 
5.5%
l1633
 
4.2%
Other values (29)10059
26.1%
Uppercase Letter
ValueCountFrequency (%)
S166
 
12.6%
A104
 
7.9%
T103
 
7.8%
C102
 
7.7%
H73
 
5.5%
I69
 
5.2%
M66
 
5.0%
B63
 
4.8%
Y52
 
3.9%
X50
 
3.8%
Other values (18)473
35.8%
Other Punctuation
ValueCountFrequency (%)
,470
36.5%
.399
31.0%
/220
17.1%
'90
 
7.0%
"60
 
4.7%
!22
 
1.7%
:15
 
1.2%
?7
 
0.5%
;4
 
0.3%
&1
 
0.1%
Decimal Number
ValueCountFrequency (%)
814
19.2%
114
19.2%
011
15.1%
210
13.7%
39
12.3%
47
9.6%
74
 
5.5%
93
 
4.1%
61
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
-56
87.5%
7
 
10.9%
1
 
1.6%
Space Separator
ValueCountFrequency (%)
8569
99.7%
 23
 
0.3%
Math Symbol
ValueCountFrequency (%)
<398
50.0%
>398
50.0%
Format
ValueCountFrequency (%)
24
100.0%
Close Punctuation
ValueCountFrequency (%)
)19
100.0%
Open Punctuation
ValueCountFrequency (%)
(19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin39842
78.5%
Common10875
 
21.4%
Cyrillic11
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e4892
12.3%
t3465
 
8.7%
a3215
 
8.1%
o2973
 
7.5%
n2801
 
7.0%
i2573
 
6.5%
s2476
 
6.2%
r2330
 
5.8%
h2115
 
5.3%
l1633
 
4.1%
Other values (47)11369
28.5%
Common
ValueCountFrequency (%)
8569
78.8%
,470
 
4.3%
.399
 
3.7%
<398
 
3.7%
>398
 
3.7%
/220
 
2.0%
'90
 
0.8%
"60
 
0.6%
-56
 
0.5%
24
 
0.2%
Other values (19)191
 
1.8%
Cyrillic
ValueCountFrequency (%)
а2
18.2%
у1
9.1%
ж1
9.1%
с1
9.1%
к1
9.1%
М1
9.1%
я1
9.1%
т1
9.1%
е1
9.1%
м1
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII50645
99.8%
None40
 
0.1%
Punctuation32
 
0.1%
Cyrillic11
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8569
16.9%
e4892
 
9.7%
t3465
 
6.8%
a3215
 
6.3%
o2973
 
5.9%
n2801
 
5.5%
i2573
 
5.1%
s2476
 
4.9%
r2330
 
4.6%
h2115
 
4.2%
Other values (67)15236
30.1%
Punctuation
ValueCountFrequency (%)
24
75.0%
7
 
21.9%
1
 
3.1%
None
ValueCountFrequency (%)
 23
57.5%
é10
25.0%
Í3
 
7.5%
ä2
 
5.0%
å1
 
2.5%
á1
 
2.5%
Cyrillic
ValueCountFrequency (%)
а2
18.2%
у1
9.1%
ж1
9.1%
с1
9.1%
к1
9.1%
М1
9.1%
я1
9.1%
т1
9.1%
е1
9.1%
м1
9.1%

_embedded_show_updated
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct65
Distinct (%)49.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1628137742
Minimum1604587145
Maximum1652080636
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2022-05-09T21:16:56.874283image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1604587145
5-th percentile1608690868
Q11610830342
median1623533863
Q31647434809
95-th percentile1651207521
Maximum1652080636
Range47493491
Interquartile range (IQR)36604467

Descriptive statistics

Standard deviation16941552.13
Coefficient of variation (CV)0.01040547841
Kurtosis-1.668597418
Mean1628137742
Median Absolute Deviation (MAD)14765017
Skewness0.1701218737
Sum2.132860443 × 1011
Variance2.870161885 × 1014
MonotonicityNot monotonic
2022-05-09T21:16:57.056879image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
160876884612
 
9.2%
161763462510
 
7.6%
164968425910
 
7.6%
16086908688
 
6.1%
16498727206
 
4.6%
16134434036
 
4.6%
16268144425
 
3.8%
16342924674
 
3.1%
16080333034
 
3.1%
16184666822
 
1.5%
Other values (55)64
48.9%
ValueCountFrequency (%)
16045871451
 
0.8%
16080333034
 
3.1%
16084101481
 
0.8%
16086908688
6.1%
160876884612
9.2%
16091813541
 
0.8%
16094684031
 
0.8%
16095364481
 
0.8%
16096716402
 
1.5%
16099236481
 
0.8%
ValueCountFrequency (%)
16520806361
0.8%
16520354301
0.8%
16520040501
0.8%
16519333631
0.8%
16519332091
0.8%
16512500711
0.8%
16512333871
0.8%
16511816551
0.8%
16505490022
1.5%
16503092011
0.8%

_links_self_href
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct131
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
https://api.tvmaze.com/episodes/1977902
 
1
https://api.tvmaze.com/episodes/2001669
 
1
https://api.tvmaze.com/episodes/2001667
 
1
https://api.tvmaze.com/episodes/2001666
 
1
https://api.tvmaze.com/episodes/2001665
 
1
Other values (126)
126 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters5109
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique131 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/1977902
2nd rowhttps://api.tvmaze.com/episodes/2015818
3rd rowhttps://api.tvmaze.com/episodes/1964000
4th rowhttps://api.tvmaze.com/episodes/1995405
5th rowhttps://api.tvmaze.com/episodes/2007760

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19779021
 
0.8%
https://api.tvmaze.com/episodes/20016691
 
0.8%
https://api.tvmaze.com/episodes/20016671
 
0.8%
https://api.tvmaze.com/episodes/20016661
 
0.8%
https://api.tvmaze.com/episodes/20016651
 
0.8%
https://api.tvmaze.com/episodes/20000731
 
0.8%
https://api.tvmaze.com/episodes/20000721
 
0.8%
https://api.tvmaze.com/episodes/19975381
 
0.8%
https://api.tvmaze.com/episodes/19975371
 
0.8%
https://api.tvmaze.com/episodes/19884051
 
0.8%
Other values (121)121
92.4%

Length

2022-05-09T21:16:57.220323image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19779021
 
0.8%
https://api.tvmaze.com/episodes/23122251
 
0.8%
https://api.tvmaze.com/episodes/19640001
 
0.8%
https://api.tvmaze.com/episodes/19954051
 
0.8%
https://api.tvmaze.com/episodes/20077601
 
0.8%
https://api.tvmaze.com/episodes/19857891
 
0.8%
https://api.tvmaze.com/episodes/20396221
 
0.8%
https://api.tvmaze.com/episodes/20396231
 
0.8%
https://api.tvmaze.com/episodes/23244271
 
0.8%
https://api.tvmaze.com/episodes/23244281
 
0.8%
Other values (121)121
92.4%

Most occurring characters

ValueCountFrequency (%)
/524
 
10.3%
p393
 
7.7%
s393
 
7.7%
e393
 
7.7%
t393
 
7.7%
o262
 
5.1%
a262
 
5.1%
i262
 
5.1%
.262
 
5.1%
m262
 
5.1%
Other values (16)1703
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3275
64.1%
Other Punctuation917
 
17.9%
Decimal Number917
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p393
12.0%
s393
12.0%
e393
12.0%
t393
12.0%
o262
8.0%
a262
8.0%
i262
8.0%
m262
8.0%
h131
 
4.0%
d131
 
4.0%
Other values (3)393
12.0%
Decimal Number
ValueCountFrequency (%)
2142
15.5%
9141
15.4%
0124
13.5%
1111
12.1%
378
8.5%
674
8.1%
871
7.7%
461
6.7%
760
6.5%
555
 
6.0%
Other Punctuation
ValueCountFrequency (%)
/524
57.1%
.262
28.6%
:131
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin3275
64.1%
Common1834
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/524
28.6%
.262
14.3%
2142
 
7.7%
9141
 
7.7%
:131
 
7.1%
0124
 
6.8%
1111
 
6.1%
378
 
4.3%
674
 
4.0%
871
 
3.9%
Other values (3)176
 
9.6%
Latin
ValueCountFrequency (%)
p393
12.0%
s393
12.0%
e393
12.0%
t393
12.0%
o262
8.0%
a262
8.0%
i262
8.0%
m262
8.0%
h131
 
4.0%
d131
 
4.0%
Other values (3)393
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII5109
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/524
 
10.3%
p393
 
7.7%
s393
 
7.7%
e393
 
7.7%
t393
 
7.7%
o262
 
5.1%
a262
 
5.1%
i262
 
5.1%
.262
 
5.1%
m262
 
5.1%
Other values (16)1703
33.3%

Interactions

2022-05-09T21:16:45.276293image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:19.202739image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:25.617074image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:28.024827image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:30.440426image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:32.705013image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:36.705499image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:38.537937image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:41.526500image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:46.606279image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:21.034778image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:26.750286image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:29.143756image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:31.499029image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:34.151603image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:37.543570image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:39.923652image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:43.465354image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:46.737106image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:21.555227image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:26.864216image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:29.377342image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:31.597823image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:34.436260image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:37.656616image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:40.047492image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:43.783918image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:46.877608image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:22.089994image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:26.979267image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:29.481111image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:31.704795image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:34.708353image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:37.767594image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:40.187931image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:43.983127image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:47.017962image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:22.591101image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:27.084420image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:29.570072image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:31.817679image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:34.975949image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:37.855055image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:40.323552image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:44.111634image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:47.740351image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:23.548418image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:27.617306image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:30.051997image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:32.326199image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:35.693528image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:38.045678image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:40.960189image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:44.803709image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:47.848272image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:23.900482image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:27.723091image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:30.147434image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:32.418470image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:35.869376image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:38.156461image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:41.073561image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:44.910998image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:47.954446image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:24.461055image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:27.831537image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:30.239902image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:32.501355image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:36.135592image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:38.287026image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:41.238402image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:45.036559image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:48.086963image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:25.093674image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:27.929408image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:30.340905image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:32.604917image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:36.418168image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:38.410444image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:41.391891image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:16:45.166795image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Correlations

2022-05-09T21:16:57.355749image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-05-09T21:16:57.725519image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-05-09T21:16:57.926805image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-05-09T21:16:58.112297image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.
2022-05-09T21:16:58.393042image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-05-09T21:16:48.411305image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
A simple visualization of nullity by column.
2022-05-09T21:16:49.236502image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-05-09T21:16:49.496886image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-05-09T21:16:49.632093image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

idurlnameseasonnumbertypeairdateairtimeairstampruntimeimagesummary_embedded_show_id_embedded_show_url_embedded_show_name_embedded_show_type_embedded_show_language_embedded_show_genres_embedded_show_status_embedded_show_runtime_embedded_show_averageRuntime_embedded_show_premiered_embedded_show_ended_embedded_show_officialSite_embedded_show_weight_embedded_show_dvdCountry_embedded_show_summary_embedded_show_updated_links_self_href
01968114https://www.tvmaze.com/episodes/1968114/po-sezonu-videodajdzest-seasonvar-6x51-vypusk-305Выпуск 3056.051.0regular2020-12-18nan2020-12-18T00:00:00+00:009.0Nonenan7847https://www.tvmaze.com/shows/7847/po-sezonu-videodajdzest-seasonvarПо сезону. Видеодайджест SeasonvarTalk ShowRussian[]Running9.09.02015-02-13nanhttp://seasonvar.ru/serial-11488-Po_sezonu_Videodajdzhest_Seasonvar.html28.0nan<p>Weekly videodaydzhest on site seasonvar.ru and creative team viruseproject.tv. In ten minutes, we talk about the most important events of the past week: look down on the set is not yet published projects, sharing the secrets of private life actors consider the prospects for the development of genres and discuss news TV industry! In videodaydzheste you will find only reliable information from Russian and foreign publications, as well as take part in choosing the best show of the month! Our weekly news videodaydzhest will suit every viewer, so gather good company with family and friends, as well as stock up on popcorn - these ten minutes you shock, delight and inform the latest news about your favorite TV projects!</p>1.651182e+09https://api.tvmaze.com/episodes/1977902
11961005https://www.tvmaze.com/episodes/1961005/cuma-2x08-seria-14Серия 142.08.0regular2020-12-18nan2020-12-18T00:00:00+00:0023.0Nonenan48402https://www.tvmaze.com/shows/48402/cumaЧума!ScriptedRussian['Comedy']Ended21.021.02020-05-292020-12-18https://www.ivi.ru/watch/chuma-202030.0nan<p><b>Plague</b> – a Comedy project about how hard it is to survive in the middle ages during the plague. This is a story about the residents of the fictional town of Hamburg, locked in a castle under quarantine. Also locked up in the castle is the Messenger William, who, in fact, brought the news of the plague.</p>1.609468e+09https://api.tvmaze.com/episodes/2015818
21989253https://www.tvmaze.com/episodes/1989253/to-so-sketci-1x07-7-vypusk7 выпуск1.07.0regular2020-12-1812:002020-12-18T00:00:00+00:0023.0Nonenan48403https://www.tvmaze.com/shows/48403/to-so-sketciТо шо скетчиVarietyRussian['Comedy']Ended10.015.02020-05-252021-03-11https://premier.one/show/to-sho-sketchi2.0nan<p>"To sho sketches" is an entertaining and unknowable show from the team of "Lena Kuka", in which there is no plot, logic, morality, and even more meaning. So turn off your brain and enjoy!</p>1.644239e+09https://api.tvmaze.com/episodes/1964000
31988013https://www.tvmaze.com/episodes/1988013/muzskaa-tema-1x02-seria-2Серия 21.02.0regular2020-12-1812:002020-12-18T00:00:00+00:0029.0Nonenan52520https://www.tvmaze.com/shows/52520/muzskaa-temaМужская темаTalk ShowRussian[]Ended30.030.02020-12-172020-12-25https://www.ivi.ru/watch/muzhskaya-tema3.0nan<p><b>Мужская тема</b> is a symbiosis of talk shows and modern podcasts, where male celebrities answer questions that concern people in the XXI century. Bright representatives of show business, theater, pop, cinema, sports, as well as Internet stars meet in the barbershop. Here, on male territory, they can openly discuss a variety of topics, sometimes seriously, and sometimes with humor. This is a chance to see the idol in a confidential communication without notes, compare his opinion with your own and hear what men really talk about when there is not a single girl around.</p>1.616723e+09https://api.tvmaze.com/episodes/1995405
42030153https://www.tvmaze.com/episodes/2030153/fox-spirit-matchmaker-9x03-episode-124Episode 1249.03.0regular2020-12-18nan2020-12-18T04:00:00+00:0010.0Nonenan20734https://www.tvmaze.com/shows/20734/fox-spirit-matchmakerFox Spirit MatchmakerAnimationChinese['Comedy', 'Anime', 'Fantasy', 'Romance']Running10.010.02015-06-26nanhttp://www.bilibili.com/bangumi/%E7%8B%90%E5%A6%96%E5%B0%8F%E7%BA%A2%E5%A8%98/64.0nan<p>Buy UCO from childhood grew up in the clan, Ichigo, but their "care" was for him a living Hell. Constant bullying, stealing the Goodies, without which Ycu can not live, and even eternal persecution, from the fair sex turned him into a goner cheapskate who wants to take revenge on his tormentors. But revenge is sweet and the path to it is thorny and to accomplish, UCU need to marry a girl Yes, as soon as possible. But when the heroes just happen? Never! And meeting with the small and the big-eared Fox Susan su su did not just destroy his plans, but starts spinning the wheel of fate that was waiting in the wings for hundreds of years!</p>1.629636e+09https://api.tvmaze.com/episodes/2007760
51972569https://www.tvmaze.com/episodes/1972569/the-wolf-1x27-episode-27Episode 271.027.0regular2020-12-18nan2020-12-18T04:00:00+00:0045.0Nonenan47912https://www.tvmaze.com/shows/47912/the-wolfThe WolfScriptedChinese['Drama', 'Romance', 'History']Ended45.045.02020-11-192021-01-04https://www.iqiyi.com/lib/m_213579814.html39.0nan<p>The story happens at the end of the Tang Dynasty, when Zhu Wen usurps the throne and establishes the Later Liang Dynasty, and he's known as Emperor Taizu. Ma Zhai Xing (Li Qin) is the daughter of an official and as a child, she befriends a young boy (Darren Wang) who lives in the mountain. One day when he saves a wolf, he accidentally falls over the cliff and is rescued by Zhu Wen. The authoritative figure adopts him as a godson and gives him the title Bo Wang. Ten years later, he saves the female lead per chance and finds her courage and intelligence resonant, and she likes that while he's in a position of power, he still has humility and kindness. She encourages him to fight for justice and he begins that journey by helping the people, stopping throne fights, etc. Even when they have conflicts, they will face those frankly. As they overcome obstacles and fight for justice, feelings deepen and they are able to reap their own happiness by each other's side.</p>1.648217e+09https://api.tvmaze.com/episodes/1985789
61972570https://www.tvmaze.com/episodes/1972570/the-wolf-1x28-episode-28Episode 281.028.0regular2020-12-18nan2020-12-18T04:00:00+00:0045.0Nonenan47912https://www.tvmaze.com/shows/47912/the-wolfThe WolfScriptedChinese['Drama', 'Romance', 'History']Ended45.045.02020-11-192021-01-04https://www.iqiyi.com/lib/m_213579814.html39.0nan<p>The story happens at the end of the Tang Dynasty, when Zhu Wen usurps the throne and establishes the Later Liang Dynasty, and he's known as Emperor Taizu. Ma Zhai Xing (Li Qin) is the daughter of an official and as a child, she befriends a young boy (Darren Wang) who lives in the mountain. One day when he saves a wolf, he accidentally falls over the cliff and is rescued by Zhu Wen. The authoritative figure adopts him as a godson and gives him the title Bo Wang. Ten years later, he saves the female lead per chance and finds her courage and intelligence resonant, and she likes that while he's in a position of power, he still has humility and kindness. She encourages him to fight for justice and he begins that journey by helping the people, stopping throne fights, etc. Even when they have conflicts, they will face those frankly. As they overcome obstacles and fight for justice, feelings deepen and they are able to reap their own happiness by each other's side.</p>1.648217e+09https://api.tvmaze.com/episodes/2039622
71910448https://www.tvmaze.com/episodes/1910448/the-founder-of-diabolism-q-1x22-escapeEscape1.022.0regular2020-12-18nan2020-12-18T04:00:00+00:005.0Nonenan49485https://www.tvmaze.com/shows/49485/the-founder-of-diabolism-qThe Founder of Diabolism QAnimationChinese['Comedy', 'Anime', 'History', 'Supernatural']Ended5.05.02020-07-312021-02-12https://v.qq.com/detail/m/mzc00200fdthd81.html60.0nan<p>The chibi spin-off takes place during the three periods of Wei Wuxian's life (adolescence, adulthood, and rebirth after death), selecting the cute, warm, and healing parts as the main contents. This series hopes to heal the audience who loves the main story of <i>Mo Dao Zu Shi</i>, but were "injured" by the melancholy plot of the drama.</p>1.621019e+09https://api.tvmaze.com/episodes/2039623
81998583https://www.tvmaze.com/episodes/1998583/mr-right-is-here-1x11-episode-11Episode 111.011.0regular2020-12-18nan2020-12-18T04:00:00+00:0045.0Nonenan52782https://www.tvmaze.com/shows/52782/mr-right-is-hereMr. Right is Here!ScriptedChinese['Drama', 'Comedy', 'Romance']Ended45.045.02020-12-102020-12-18nan15.0nan<p>‎The fashion company faced a crisis. Sun Chi, the young owner of the company, at a critical moment took over the management and became the new CEO. He promised his father that in three months he would be able to promote the project "promoting fashion" that will help to get out of the crisis. ‎ </p><p>‎Gio Intao, who wanted to be the queen of the fashion industry, by coincidence got into the company and became subordinate to the "devil", a young gene. Director Sun Chi.‎   </p><p>‎Sun Chi and Xiao Intao led a fashion company to resolve the crisis and open new markets, allowing Chinese fashion brands to enter the global market step by step. At the same time, they begin to feel each other.‎</p>1.609672e+09https://api.tvmaze.com/episodes/2324427
91998584https://www.tvmaze.com/episodes/1998584/mr-right-is-here-1x12-episode-12Episode 121.012.0regular2020-12-18nan2020-12-18T04:00:00+00:0045.0Nonenan52782https://www.tvmaze.com/shows/52782/mr-right-is-hereMr. Right is Here!ScriptedChinese['Drama', 'Comedy', 'Romance']Ended45.045.02020-12-102020-12-18nan15.0nan<p>‎The fashion company faced a crisis. Sun Chi, the young owner of the company, at a critical moment took over the management and became the new CEO. He promised his father that in three months he would be able to promote the project "promoting fashion" that will help to get out of the crisis. ‎ </p><p>‎Gio Intao, who wanted to be the queen of the fashion industry, by coincidence got into the company and became subordinate to the "devil", a young gene. Director Sun Chi.‎   </p><p>‎Sun Chi and Xiao Intao led a fashion company to resolve the crisis and open new markets, allowing Chinese fashion brands to enter the global market step by step. At the same time, they begin to feel each other.‎</p>1.609672e+09https://api.tvmaze.com/episodes/2324428

Last rows

idurlnameseasonnumbertypeairdateairtimeairstampruntimeimagesummary_embedded_show_id_embedded_show_url_embedded_show_name_embedded_show_type_embedded_show_language_embedded_show_genres_embedded_show_status_embedded_show_runtime_embedded_show_averageRuntime_embedded_show_premiered_embedded_show_ended_embedded_show_officialSite_embedded_show_weight_embedded_show_dvdCountry_embedded_show_summary_embedded_show_updated_links_self_href
1211978799https://www.tvmaze.com/episodes/1978799/your-home-1x03-yourhomekwekkwek#YourHomeKwekKwek1.03.0regular2020-12-18nan2020-12-18T12:00:00+00:0022.0{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/289/723807.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/289/723807.jpg'}<p>"I am not you". They will feel what's missing from their lives. Someone will find a way to solve a quite impossible problem. </p>52196https://www.tvmaze.com/shows/52196/your-homeYour HomeScriptedTagalog['Drama', 'Romance']Ended30.023.02020-12-042021-01-22https://www.youtube.com/c/ArcanaStudiosInc/30.0nan<p>Imagine a world where boys' love is normal. You don't have to prove yourself more just because you're gay or different. No judgy stares and harsh whispers from strangers or even from family. Our story is about the coming of age of two boys that are feeling alone and their adventures to find a place they can call home. Welcome to our world. Welcome to Your Home.</p>1.649367e+09https://api.tvmaze.com/episodes/2234297
1221985202https://www.tvmaze.com/episodes/1985202/handmade-love-1x03-the-reason-we-should-break-upThe Reason We Should Break Up1.03.0regular2020-12-18nan2020-12-18T12:00:00+00:0014.0{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/289/723200.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/289/723200.jpg'}nan52412https://www.tvmaze.com/shows/52412/handmade-loveHandmade LoveScriptedKorean['Drama', 'Fantasy', 'Romance']Ended15.017.02020-12-112021-01-05https://www.youtube.com/playlist?list=PLRXdsS5E_8i3FJ_o7VF0TFb9SUdWk54iW27.0nan<p>The god Woo Beun can only return to heaven after comforting humans with clothes. He is running a tailor shop called "Handmade Love" with his servant Joy when Han Sa Rang visits the tailor shop after hearing the news that her boyfriend of 7 years will get married. Together, they will heal the wounds of their guests.</p>1.609924e+09https://api.tvmaze.com/episodes/2236494
1231985311https://www.tvmaze.com/episodes/1985311/daughters-1x07-episode-7Episode 71.07.0regular2020-12-1820:002020-12-18T12:00:00+00:0050.0Nonenan52415https://www.tvmaze.com/shows/52415/daughtersDaughtersScriptedThai['Drama', 'Crime', 'Family']Running50.050.02020-12-04nanhttps://www.iq.com/play/1n40eysnffc15.0nan<p>This is a story of four curious girls each of whose problems originates from family problems and lack of familial love. The only remedy for them is friendship that helps unwound their trauma. They leave all their troubles behind and create their own world upon which drugs grant them the way out, and along that path they are confronted with their fates together.There is just a drug to soothe the heart. Until the end, it became a huge problem that they had never expected from a small step that wanted to try to take it too far to go back. When they realized it again, they could only feel "regretting" the moment of them life. The bad thing And it's a big lesson at the price of your whole life.</p>1.623534e+09https://api.tvmaze.com/episodes/1977423
1241985312https://www.tvmaze.com/episodes/1985312/daughters-1x08-episode-8Episode 81.08.0regular2020-12-1820:002020-12-18T12:00:00+00:0050.0Nonenan52415https://www.tvmaze.com/shows/52415/daughtersDaughtersScriptedThai['Drama', 'Crime', 'Family']Running50.050.02020-12-04nanhttps://www.iq.com/play/1n40eysnffc15.0nan<p>This is a story of four curious girls each of whose problems originates from family problems and lack of familial love. The only remedy for them is friendship that helps unwound their trauma. They leave all their troubles behind and create their own world upon which drugs grant them the way out, and along that path they are confronted with their fates together.There is just a drug to soothe the heart. Until the end, it became a huge problem that they had never expected from a small step that wanted to try to take it too far to go back. When they realized it again, they could only feel "regretting" the moment of them life. The bad thing And it's a big lesson at the price of your whole life.</p>1.623534e+09https://api.tvmaze.com/episodes/1976649
1251985473https://www.tvmaze.com/episodes/1985473/you-complete-me-1x17-episode-17Episode 171.017.0regular2020-12-1820:002020-12-18T12:00:00+00:0045.0Nonenan52421https://www.tvmaze.com/shows/52421/you-complete-meYou Complete MeScriptedChinese['Drama', 'Romance']Ended45.045.02020-12-022021-01-14nan18.0nan<p>‎At the end of the 20th century, due to the sudden decision of Xin Shensheng, gao Shan's business went bankrupt. Gao Shan wants to prove his father's innocence, but on his way suddenly falls in love with the daughter of Xin Shensheng, Tsin Waugh. Learning about the intentions of Gao Shan, Xin Shansheng makes him quit his job. ‎<br /><br />‎Gao Shan decides to go to Hong Kong to start from scratch, where he meets a benefactor and earns his first million in his life. Under the guidance of a mentor, he goes to Beijing and becomes a well-known investor. Soon Gao Shan meets Tsin Vo, who became a financial headhunter. Can love help them find their way to each other again? ‎<br /><br />‎Based on the novel by Xiao Moli "Little Storm 1.0"‎</p>1.619633e+09https://api.tvmaze.com/episodes/2005096
1261985474https://www.tvmaze.com/episodes/1985474/you-complete-me-1x18-episode-18Episode 181.018.0regular2020-12-1820:002020-12-18T12:00:00+00:0045.0Nonenan52421https://www.tvmaze.com/shows/52421/you-complete-meYou Complete MeScriptedChinese['Drama', 'Romance']Ended45.045.02020-12-022021-01-14nan18.0nan<p>‎At the end of the 20th century, due to the sudden decision of Xin Shensheng, gao Shan's business went bankrupt. Gao Shan wants to prove his father's innocence, but on his way suddenly falls in love with the daughter of Xin Shensheng, Tsin Waugh. Learning about the intentions of Gao Shan, Xin Shansheng makes him quit his job. ‎<br /><br />‎Gao Shan decides to go to Hong Kong to start from scratch, where he meets a benefactor and earns his first million in his life. Under the guidance of a mentor, he goes to Beijing and becomes a well-known investor. Soon Gao Shan meets Tsin Vo, who became a financial headhunter. Can love help them find their way to each other again? ‎<br /><br />‎Based on the novel by Xiao Moli "Little Storm 1.0"‎</p>1.619633e+09https://api.tvmaze.com/episodes/2005098
1271986159https://www.tvmaze.com/episodes/1986159/the-burning-river-1x09-episode-9Episode 91.09.0regular2020-12-1820:002020-12-18T12:00:00+00:0045.0Nonenan52451https://www.tvmaze.com/shows/52451/the-burning-riverThe Burning RiverScriptedChinese['Drama', 'Action', 'Thriller']Running45.045.02020-12-11nanhttps://v.youku.com/v_show/id_XNDk1MzY2NzgwNA==.html?spm=a2h0c.8166622.PhoneSokuProgram_1.dtitle&s=aaed627feea749d7a99d24.0nan<p>Two boggling mysteries have occured in a small town in Xinan. A female police captain joins hands with a young detective to conduct an investigation. Although a clear motive can be seen, the two discover a series of unknown secrets.</p><p>One case involves a late-night ride hailed through an online platform that goes terribly wrong. As more and more clues resurface, the cases in the hands of the police hands become complicated and entangled. In a desperate attempt to find the real culprit, events closely link the past, present and future of the small town.</p>1.608033e+09https://api.tvmaze.com/episodes/2005099
1281986160https://www.tvmaze.com/episodes/1986160/the-burning-river-1x10-episode-10Episode 101.010.0regular2020-12-1820:002020-12-18T12:00:00+00:0045.0Nonenan52451https://www.tvmaze.com/shows/52451/the-burning-riverThe Burning RiverScriptedChinese['Drama', 'Action', 'Thriller']Running45.045.02020-12-11nanhttps://v.youku.com/v_show/id_XNDk1MzY2NzgwNA==.html?spm=a2h0c.8166622.PhoneSokuProgram_1.dtitle&s=aaed627feea749d7a99d24.0nan<p>Two boggling mysteries have occured in a small town in Xinan. A female police captain joins hands with a young detective to conduct an investigation. Although a clear motive can be seen, the two discover a series of unknown secrets.</p><p>One case involves a late-night ride hailed through an online platform that goes terribly wrong. As more and more clues resurface, the cases in the hands of the police hands become complicated and entangled. In a desperate attempt to find the real culprit, events closely link the past, present and future of the small town.</p>1.608033e+09https://api.tvmaze.com/episodes/2005100
1291986161https://www.tvmaze.com/episodes/1986161/the-burning-river-1x11-episode-11Episode 111.011.0regular2020-12-1820:002020-12-18T12:00:00+00:0045.0Nonenan52451https://www.tvmaze.com/shows/52451/the-burning-riverThe Burning RiverScriptedChinese['Drama', 'Action', 'Thriller']Running45.045.02020-12-11nanhttps://v.youku.com/v_show/id_XNDk1MzY2NzgwNA==.html?spm=a2h0c.8166622.PhoneSokuProgram_1.dtitle&s=aaed627feea749d7a99d24.0nan<p>Two boggling mysteries have occured in a small town in Xinan. A female police captain joins hands with a young detective to conduct an investigation. Although a clear motive can be seen, the two discover a series of unknown secrets.</p><p>One case involves a late-night ride hailed through an online platform that goes terribly wrong. As more and more clues resurface, the cases in the hands of the police hands become complicated and entangled. In a desperate attempt to find the real culprit, events closely link the past, present and future of the small town.</p>1.608033e+09https://api.tvmaze.com/episodes/2005101
1301986162https://www.tvmaze.com/episodes/1986162/the-burning-river-1x12-episode-12Episode 121.012.0regular2020-12-1820:002020-12-18T12:00:00+00:0045.0Nonenan52451https://www.tvmaze.com/shows/52451/the-burning-riverThe Burning RiverScriptedChinese['Drama', 'Action', 'Thriller']Running45.045.02020-12-11nanhttps://v.youku.com/v_show/id_XNDk1MzY2NzgwNA==.html?spm=a2h0c.8166622.PhoneSokuProgram_1.dtitle&s=aaed627feea749d7a99d24.0nan<p>Two boggling mysteries have occured in a small town in Xinan. A female police captain joins hands with a young detective to conduct an investigation. Although a clear motive can be seen, the two discover a series of unknown secrets.</p><p>One case involves a late-night ride hailed through an online platform that goes terribly wrong. As more and more clues resurface, the cases in the hands of the police hands become complicated and entangled. In a desperate attempt to find the real culprit, events closely link the past, present and future of the small town.</p>1.608033e+09https://api.tvmaze.com/episodes/2005102